introduction to linear algebra 5th edition 中译 -回复

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1. Numerical linear algebra

1. Numerical linear algebra
(Stoer & Bulirsch, Cheney & Kincaid)
1. Methods for initial value problems for ordinary di erential equations: Runge-Kutta and Adams methods.
2. Methods with automatic step-size control for Runge-Kutta and Adams methods. 3. Basic concepts of stability of the multistep methods for ODE's and systems.
7. Finite element method
(Joix)
1. Weak (variational) formulation and characterization of the energy space: essential and natural boundary condition.
3. Eigenvalues and eigenvectors of matrices (minimax methods for symmetric matrices, power method, QR method). Singular value decomposition and its basic properties.
estimates (Courant condition). 3. Error estimates
6. Numerical methods for elliptic problems
(Ames, Striktwerda)
1. Finite di erences and nite volumes: approximation of the equation and the boundary conditions, higher order schemes.

PDF分享:国外优秀数学教材选评

PDF分享:国外优秀数学教材选评

PDF分享:国外优秀数学教材选评《国外优秀数学教材选评》推荐书⽬下载具体内容请查看原:或者注:1. 由于国外教材更新频繁,其中⾮数学专业教材尤为显著,相较于原版本,其中有部分版本已经更新,以下提供的是尽所能搜索到的最新版本2. 所有⽂件都来源⽹络,余不敢独享,特整理发布。

尽⼒择⾼质量版本分享,但难免有所疏漏,烦请提出宝贵意见3. 由于多数书籍出版已多年,购买确有不便,PDF实为⽆奈之举,望有能之⼠可以⽀持正版4. ⽂件为公开分享,链接失效请评论或联系,为了防⽌分享被封禁,添加了密码压缩,密码为:5. ⼗年之前的书籍许多使⽤了DjVu格式+OCR,其质量略⾼于对应扫描PDF,也可以转化为PDF2.2.1 微积分1. Calculus | Hughes Hallet,Gleason,McCallum et al. |2. Calculus : Early Transcendentals | James Stewart | /3. Advanced Calculus | Patrick M. Fitzpatrick |4. Calculus : Early Transcendental functions | Ron Larson, Robert P Hostetler, Bruce H Edwards |5. Calculus One And Sevel Variables | Saturnino L Salas, Einar Hille, Garret J Etgen |6. Calculus | Monty J Strauss, Gerald L Bradley, Karl J Smith |7. Calculus | Dale E Varberg, Edwin J Purcell, Steven E Rigdon |2.2 线性代数1. Linear Algebra and its Applications | Gilbert Strang |2. Introduction to Linear Algebra | Gilbert Strang |3. Linear Algebra and its Applications | David C. Lay |4. Elementary Linear Algebra | Howard Anton | 同下5. Elementary Linear Algebra (application version) | Howard Anton |6. Linear Algebra with Applications | Otto Bretscher |7. Linear Algebra with Applications | Steven J. Leon |8. Linear Algebra Done Right | S. Axler | /2.3 其它1. Differential Equations | P. Blanchard, R. Devaney, G. Hall |2. Concrete Mathematics | R.Graham, D.Knuth, O.Patashnik |3. Discrete Mathematics | Dossey,Otto,Spence,Vanden Eynden |3.1. Introducton to Analysis | Arthur Mattuck |2. Mathematical Analysis | Tom M. Apostol |3. Principle of Mathematical Analysis | Walter Rudin |4. Advanced Calculus | Patrick M. Fitzpatrick |5. Advanced Calculus | Wilfred Kaplan |6. Advanced Calculus | Lynn H. Loomis, Shlomo Sternberg |7. Problems and Theorems in Analysis | George Po l ya, Ga b or Szego|8. Functional Analysis | Walter Rudin |4.1. Complex Analysis | Lars V. Ahlfors |2. Introduction to complex analysis | Kunihiko Kodaira |3. Functions of One Complex Variable | John B. Conway |4. Complex Analysis | Serge Lang |5.1. An Introduction to Complex Analysis in Several Variables | Lars Hörmander |2. Introduction to Complex Analysis Part II, Functions in Several Variables | B. V. Shabat |3. Topics in Complex Function Theory | Carl L. Siegel |6.1. Linear Algebra | K. Hoffmann and R. Kunze |2. Lectures on Linear Algebra | Gelfand |3. Linear Algebra Gems | David Carlson, Charles R. Johnson,David C. Lay, A. Duane Porter |4. Algebra | Michael Artin |5. Codes and Curves | Judy Walker |6. Introduction to Commutative Algebra | Michael Atiyah & I.G.MacDonald |7. Hopf Algebra | Moss E. Sweedler |7.1. Elementary Methods in Number Theory | Melvyn B.Nathanson |2. A Course in Arithmetic | J.-P. Serre |3. Introduction to Analytic Number Theory | Tom Apostol |8.1. An Invitation to Algebraic Geometry | K.Smith etc. |2. Introduction to Commutative Algebra and Algebraic Geometry | Ernst Kunz |3. Basic Algebraic Geometry | Shafarevich |4. Algebraic Geometry | Robin Hartshorne |5. Principles of Algebraic Geometry | Phillip Griffiths, Joseph Harris |6. The Red Book of Varieties and Schemes | David Mumford |7. Compact Complex Surfaces | W.P. Barth, K. Hulek, C.A.M. Peters, A. Van de Ven |9.1. Elements of Algebraic Topology | James R. Munkres |2. Lecture Notes on Elementary Topology and Geometry | Singer & Thorpe |3. Topology from the differentiable viewpoint | John Milnor |4. Algebraic topology | Hatcher |5. Differential forms in algebraic topology | Bott & Tu |6. Knot thoery | Livingston |7. Riemannian Geometry | M.P. Do Carmo |8. Foundations of Differential Geometry (in two volumes) | Shoshichi Kobayashi & Katsumi Nomizu |9. Introduction to Lie groups and Lie algebras | A.A.Sagle & R.E.Walde |10.1. Hyperbolic Partial Differential Equations | Peter D. Lax |2. Partial Differential Equations, An Introduction | Walter A. Strauss |3. Partial Differential Equations | Lawrence C. Evans |4. Partial Differential Equations | Fritz John |11.1. An Introduction to probability theory and its applications, Vol 1 | William Feller |2. A course in Probability Theory | Kai Lai Chung |12.1. Numerical Optimization | J. Nocedal & S. Wright |13.1. Berkeley Problems in Mathematics | Souza & Silva |2. Putnam and Beyond | Gelca & Andreescu |另外推荐:。

最全大学课程英文名称

最全大学课程英文名称

高级语言程序设计Advanced Language Programme Design工程造价管理Project Pricing Management工业行业技术评估概论Introduction to Industrial Technical Evaluation 公共关系Public Relations公关礼仪Etiquette for Public Relations管理沟通Managerial Communication国际关系与政治International Relationship and Politics国际技术贸易International Technology Trade机械制图Mechanical Drawing计算机科学Computer Science技术创新Technological Innovation技术经济Technological Economics价格学Pricing建筑项目预算Constructive Project Budgeting金融管理软件Financial Management Software经济文献检索Economic Document Searching经济文写作Economic Article Writing经贸科研论文与写作Research Project on Economics & Trade伦理学Ethics逻辑学Logic社会保障Social Security社会调查Social Survey社会学Sociology世界经济概论Introduction to World Economy世界经贸地理World Geography for Economics and Trade世界市场行情World Market Survey世界政治经济与国际关系World Politics, Economy and International Relations 数据结构Database Structure数据库管理Database Management数据库及其应用Database and Applications数据模型与决策Digital Models and Decision-making外国经济地理Economic Geography of Foreign Countries外国经济史History of Foreign Economies外贸函电Business Correspondence for Foreign Trade外贸口语Oral English for Foreign Trade外贸实务Foreign Trade Practices物流运输计划管理Logistics Planning & management系统工程System Engineering现代国际政治与经济Contemporary International Politics and Economics信息分析Information Analysis信息技术与新组织Information Technology and New Organisations形式逻辑Formal Logic英语经贸文章选读Selected English Readings of Economic and Trade Literature营销管理Marketing Management营运管理Operation Management运筹学Operations Research战略管理Strategic Management职业道德伦理Professional Ethics中国对外经贸政策与投资环境Chinese Foreign Trade Policy and Investment Environment中国对外贸易史History of Chinese Foreign Trade中国外贸概论Introduction to Chinese Foreign Trade资刊选读Selected Reading from Foreign Magazines组织行为学Organisational Behaviour大学课程英文名称(做英文成绩单有用)Advanced Computational Fluid Dynamics 高等计算流体力学Advanced Mathematics 高等数学Advanced Numerical Analysis 高等数值分析Algorithmic Language 算法语言Analogical Electronics 模拟电子电路Artificial Intelligence Programming 人工智能程序设计Audit 审计学Automatic Control System 自动控制系统Automatic Control Theory 自动控制理论Auto-Measurement Technique 自动检测技术Basis of Software Technique 软件技术基础Calculus 微积分Catalysis Principles 催化原理Chemical Engineering Document Retrieval 化工文献检索Circuitry 电子线路College English 大学英语College English Test (Band 4) CET-4College English Test (Band 6) CET-6College Physics 大学物理Communication Fundamentals 通信原理Comparative Economics 比较经济学Complex Analysis 复变函数论Computational Method 计算方法Computer Graphics 图形学原理Computer Interface Technology 计算机接口技术Contract Law 合同法Cost Accounting 成本会计Circuit Measurement Technology 电路测试技术Database Principles 数据库原理Design & Analysis System 系统分析与设计Developmental Economics 发展经济学Digital Electronics 数字电子电路Digital Image Processing 数字图像处理Digital Signal Processing 数字信号处理Econometrics 经济计量学Economical Efficiency Analysis for Chemical Technology 化工技术经济分析Economy of Capitalism 资本主义经济Electromagnetic Fields & Magnetic Waves 电磁场与电磁波Electrical Engineering Practice 电工实习Enterprise Accounting 企业会计学Equations of Mathematical Physics 数理方程Experiment of College Physics 物理实验Experiment of Microcomputer 微机实验Experiment in Electronic Circuitry 电子线路实验Fiber Optical Communication System 光纤通讯系统Finance 财政学Financial Accounting 财务会计Fine Arts 美术Functions of a Complex Variable 单复变函数Functions of Complex Variables 复变函数Functions of Complex Variables & Integral Transformations 复变函数与积分变换Fundamentals of Law 法律基础Fuzzy Mathematics 模糊数学General Physics 普通物理Graduation Project(Thesis) 毕业设计(论文)Graph theory 图论Heat Transfer Theory 传热学History of Chinese Revolution 中国革命史Industrial Economics 工业经济学Information Searches 情报检索Integral Transformation 积分变换Intelligent robot(s); Intelligence robot 智能机器人International Business Administration 国际企业管理International Clearance 国际结算International Finance 国际金融International Relation 国际关系International Trade 国际贸易Introduction to Chinese Tradition 中国传统文化Introduction to Modern Science & Technology 当代科技概论Introduction to Reliability Technology 可靠性技术导论Java Language Programming Java 程序设计Lab of General Physics 普通物理实验Linear Algebra 线性代数Management Accounting 管理会计学Management Information System 管理信息系统Mechanic Design 机械设计Mechanical Graphing 机械制图Merchandise Advertisement 商品广告学Metalworking Practice 金工实习Microcomputer Control Technology 微机控制技术Microeconomics & Macroeconomics 西方经济学Microwave Technique 微波技术Military Theory 军事理论Modern Communication System 现代通信系统Modern Enterprise System 现代企业制度Monetary Banking 货币银行学Motor Elements and Power Supply 电机电器与供电Moving Communication 移动通讯Music 音乐Network Technology 网络技术Numeric Calculation 数值计算Oil Application and Addition Agent 油品应用及添加剂Operation & Control of National Economy 国民经济运行与调控Operational Research 运筹学Optimum Control 最优控制Petroleum Chemistry 石油化学Petroleum Engineering Technique 石油化工工艺学Philosophy 哲学Physical Education 体育Political Economics 政治经济学Primary Circuit (反应堆)一回路Principle of Communication 通讯原理Principle of Marxism 马克思主义原理Principle of Mechanics 机械原理Principle of Microcomputer 微机原理Principle of Sensing Device 传感器原理Principle of Single Chip Computer 单片机原理Principles of Management 管理学原理Probability Theory & Stochastic Process 概率论与随机过程Procedure Control 过程控制Programming with Pascal Language Pascal语言编程Programming with C Language C语言编程Property Evaluation 工业资产评估Public Relation 公共关系学Pulse & Numerical Circuitry 脉冲与数字电路Refinery Heat Transfer Equipment 炼厂传热设备Satellite Communications 卫星通信Semiconductor Converting Technology 半导体变流技术Set Theory 集合论Signal & Linear System 信号与线性系统Social Research 社会调查SPC Exchange Fundamentals 程控交换原理Specialty English 专业英语Statistics 统计学Stock Investment 证券投资学Strategic Management for Industrial Enterprises 工业企业战略管理Technological Economics 技术经济学Television Operation 电视原理Theory of Circuitry 电路理论Turbulent Flow Simulation and Application 湍流模拟及其应用Visual C++ Programming Visual C++程序设计Windows NT Operating System Principles Windows NT操作系统原理Word Processing 数据处理姓名NAME性别SEX入学时间1ST TERM ENROLLED IN系别DEPARTMENT专业SPECIALITY毕业时间GRADUATION DA TE19XX-19YY学年度第一/二学期1st/2nd TERM. 19XX-19YY课程名称COURSE TITLE学分CREDIT成绩GRADE高等数学Advanced Mathematics工程数学Engineering Mathematics中国革命史History of Chinese Revolutionary程序设计Programming Design机械制图Mechanical Drawing社会学Sociology体育Physical Education物理实验Physical Experiments电路Circuit物理Physics哲学Philosophy法律基础Basis of Law理论力学Theoretical Mechanics材料力学Material Mechanics电机学Electrical Machinery政治经济学Political Economy自动控制理论Automatic Control Theory模拟电子技术基础Basis of Analogue Electronic Technique 数字电子技术Digital Electrical Technique电磁场Electromagnetic Field微机原理Principle of Microcomputer企业管理Business Management专业英语Specialized English可编程序控制技术Controlling Technique for Programming 金工实习Metal Working Practice毕业实习Graduation Practice。

课程名称英文翻译解答

课程名称英文翻译解答

Advanced Computational Fluid Dynamics 高等计算流体力学Advanced Mathematics 高等数学Advanced Numerical Analysis 高等数值分析Algorithmic Language 算法语言Analogical Electronics 模拟电子电路Artificial Intelligence Programming 人工智能程序设计Audit 审计学Automatic Control System 自动控制系统Automatic Control Theory 自动控制理论Auto-Measurement Technique 自动检测技术Basis of Software Technique 软件技术基础Calculus 微积分Catalysis Principles 催化原理Chemical Engineering Document Retrieval 化工文献检索Circuitry 电子线路College English 大学英语College English Test (Band 4) CET-4College English Test (Band 6) CET-6College Physics 大学物理Communication Fundamentals 通信原理Comparative Economics 比较经济学Complex Analysis 复变函数论Computational Method 计算方法Computer Graphics 图形学原理computer organization 计算机组成原理computer architecture 计算机系统结构Computer Interface Technology 计算机接口技术Contract Law 合同法Cost Accounting 成本会计Circuit Measurement Technology 电路测试技术Database Principles 数据库原理Design & Analysis System 系统分析与设计Developmental Economics 发展经济学discrete mathematics 离散数学Digital Electronics 数字电子电路Digital Image Processing 数字图像处理Digital Signal Processing 数字信号处理Econometrics 经济计量学Economical Efficiency Analysis for Chemical Technology 化工技术经济分析Economy of Capitalism 资本主义经济Electromagnetic Fields & Magnetic Waves 电磁场与电磁波Electrical Engineering Practice 电工实习Enterprise Accounting 企业会计学Equations of Mathematical Physics 数理方程Experiment of College Physics 物理实验Experiment of Microcomputer 微机实验Experiment in Electronic Circuitry 电子线路实验Fiber Optical Communication System 光纤通讯系统Finance 财政学Financial Accounting 财务会计Fine Arts 美术Functions of a Complex Variable 单复变函数Functions of Complex Variables 复变函数Functions of Complex Variables & Integral Transformations 复变函数与积分变换Fundamentals of Law 法律基础Fuzzy Mathematics 模糊数学General Physics 普通物理Graduation Project(Thesis) 毕业设计(论文)Graph theory 图论Heat Transfer Theory 传热学History of Chinese Revolution 中国革命史Industrial Economics 工业经济学Information Searches 情报检索Integral Transformation 积分变换Intelligent robot(s); Intelligence robot 智能机器人International Business Administration 国际企业管理International Clearance 国际结算International Finance 国际金融International Relation 国际关系International Trade 国际贸易Introduction to Chinese Tradition 中国传统文化Introduction to Modern Science & Technology 当代科技概论Introduction to Reliability Technology 可靠性技术导论Java Language Programming Java 程序设计Lab of General Physics 普通物理实验Linear Algebra 线性代数Management Accounting 管理会计学Management Information System 管理信息系统Mechanic Design 机械设计Mechanical Graphing 机械制图Merchandise Advertisement 商品广告学Metalworking Practice 金工实习Microcomputer Control Technology 微机控制技术Microeconomics & Macroeconomics 西方经济学Microwave Technique 微波技术Military Theory 军事理论Modern Communication System 现代通信系统Modern Enterprise System 现代企业制度Monetary Banking 货币银行学Motor Elements and Power Supply 电机电器与供电Moving Communication 移动通讯Music 音乐Network Technology 网络技术Numeric Calculation 数值计算Oil Application and Addition Agent 油品应用及添加剂Operation & Control of National Economy 国民经济运行与调控Operational Research 运筹学Optimum Control 最优控制Petroleum Chemistry 石油化学Petroleum Engineering Technique 石油化工工艺学Philosophy 哲学Physical Education 体育Political Economics 政治经济学principle of compiling 编译原理Primary Circuit (反应堆)一回路Principle of Communication 通讯原理Principle of Marxism 马克思主义原理Principle of Mechanics 机械原理Principle of Microcomputer 微机原理Principle of Sensing Device 传感器原理Principle of Single Chip Computer 单片机原理Principles of Management 管理学原理Probability Theory & Stochastic Process 概率论与随机过程Procedure Control 过程控制Programming with Pascal Language Pascal 语言编程Programming with C Language C 语言编程Property Evaluation 工业资产评估Public Relation 公共关系学Pulse & Numerical Circuitry 脉冲与数字电路Refinery Heat Transfer Equipment 炼厂传热设备Satellite Communications 卫星通信Semiconductor Converting Technology 半导体变流技术Set Theory 集合论Signal & Linear System 信号与线性系统Social Research 社会调查software engineering 软件工程SPC Exchange Fundamentals 程控交换原理Specialty English 专业英语Statistics 统计学Stock Investment 证券投资学Strategic Management for Industrial Enterprises 工业企业战略管理Technological Economics 技术经济学Television Operation 电视原理 Theory of Circuitry 电路理论 Turbulent Flow Simulation and Application 湍流模拟及其应用 Visual C++ Programming Visual C++ 程序设计 Windows NT Operating System Principles Windows NT 操作系统原理 Word Processing 数据处理 生物物理学 Biophysics 真空冷冻干燥技术 Vacuum Freezing & Drying Technology 16 位微机 16 Digit Microcomputer ALGOL BASIC BASIC C 语言CAD 概论 Introduction to CADCAD/CAM CAD/CAMCOBOL 语言 COBOL LanguageCOBOL语言程序设计 COBOL LanguageProgram DesigningC 与 UNIX 环境 C Language & Unix EnvironmentC 语言与生物医学信息处理 C Language & Biomedical Information Processing dBASE 川课程设计 C ourse Exercise in dBASE 川FORTRAN 语言 FORTRAN Language IBM-PC/XT Fundamentals of Microcomputer IBM-PC/XT IBM-PC 微机原理 Fundamentals of Microcomputer IBM-PCLSI 设计基础 Basic of LSI Designing PASCAL 大型作业 PASCAL Wide Range WorkingPASCAL 课程设计 Course Exercise in PASCAL X 射线与电镜 X-ray & Electric Microscope Z-80 汇编语言程序设计 Z-80 Pragramming in Assembly Languages 板壳理论 Plate Theory 板壳力学半波实验 Semiwave Experiment 半导体变流技术 Semiconductor Converting Technology 半导体材料 Semiconductor Materials 半导体测量 Measurement of Semiconductors 半导体瓷敏元件Semiconductor Porcelain-Sensitive Elements半导体光电子学 Semiconductor Optic Electronics半导体化学 Semiconductor Chemistry 半导体激光器 Semiconductor Laser Unit 半导体集成电路 Semiconductor Integrated Circuitry半导体理论 Semiconductive Theory 半导体器件 Semiconductor Devices 半导体器件工艺原理 Technological Fundamentals of Semiconductor Device 半导体物理 Semiconductor Physics 半导体专业 Semiconduction Specialty语言 ALGOL Language语言 BASIC Language 语言及应用 BASICLanguage & Application C LanguagePlate Mechanics半导体专业实验 Specialty Experiment of Semiconductor 薄膜光学 Film Optics 报告文学专题 Special Subject On Reportage 报刊编辑学 Newspaper & Magazine Editing 报纸编辑学Newspaper Editing 泵与风机 泵与水机 毕业设计 编译方法 编译技术 编译原理 变电站的微机检测与控制 变分法与张量 Calculus of Variations & Tensor 变分学 Calculus of Variations 变质量系统热力学与新型回转压 Variable Quality System Thermal Mechanics & Neo-Ro 表面活性物质 Surface ReactiveMaterials 并行算法ParallelAlgorithmic波谱学WaveSpectrum 材料的力学性能测试 Measurement of Material Mechanical Performance 材料力学 Mechanics of Materials 财务成本管理 Financial Cost Management 财政学 Public Finance 财政与金融 Finance & Banking 财政与信贷 Finance & Credit 操作系统 Disk Operating System 操作系统课程设计 Course Design in Disk Operating System 操作系统原理 Fundamentals of Disk Operating System 策波测量技术 Technique of Whip Wave Measurement 测量原理与仪器设计 Measurement Fundamentals & Meter Design 测试技术 Testing Technology 测试与信号变换处理 Testing & Signal Transformation Processing 产业经济学 Industrial Economy 产业组织学 Industrial Organization Technoooligy 场论 Field Theory 常微分方程 Ordinary Differentical Equations 超导磁体及应用 Superconductive Magnet & Application 超导及应用Superconductive & Application 超精微细加工 Super-Precision & Minuteness Processing 城市规划原理 Fundamentals of City Planning 城市社会学 Urban Sociology 成组技术 Grouping Technique 齿轮啮合原理 Principles of Gear Connection 冲击测量及误差 PunchingMeasurement & Error 冲压工艺 Sheet Metal Forming Technology Pumps and FansPumps & Water Turbines Graduation Thesis Methods of Compiling Technique of CompilingFundamentals of Compiling Computer Testing & Control in Transformer Substation抽象代数Abstract Algebra 传动概论Introduction to Transmission 传感器与检测技术Sensors & Testing Technology 传感器原理Fundamentals of Sensors 传感器原理及应用Fundamentals of Sensors & Application 传热学Heat Transfer 传坳概论Introduction to Pass Col 船舶操纵Ship Controling 船舶电力系统Ship Electrical Power System 船舶电力系统课程设计Course Exercise in Ship Electrical Power System 船舶电气传动自动化Ship Electrified Transmission Automation 船舶电站Ship Power Station 船舶动力装置Ship Power Equipment 船舶概论Introduction to Ships 船舶焊接与材料Welding & Materials on Ship 船舶机械控制技术Mechanic Control Technology for Ships 船舶机械拖动Ship Mechamic Towage 船舶建筑美学Artistic Designing of Ships 船舶结构力学Structual Mechamics for Ships 船舶结构与制图Ship Structure & Graphing 船舶静力学Ship Statics 船舶强度与结构设计Designing Ship Intensity & Structure 船舶设计原理Principles of Ship Designing 船舶推进Ship Propeling 船舶摇摆Ship Swaying 船舶阻力Ship Resistance 船体建造工艺Ship-Building Technology 船体结构Ship Structure 船体结构图船体振动学创造心理学磁测量技术磁传感器Magnetic Sensor 磁存储设备设计原理Fundamental Design of Magnetic Memory Equipment 磁记录技术Magnetographic Technology 磁记录物理Magnetographic Physics 磁路设计与场计算Magnetic Path Designing & Magnetic Field Calculati 磁盘控制器Magnetic Disk Controler 磁性材料Magnetic Materials 磁性测量Magnetic Measurement 磁性物理Magnetophysics 磁原理及应用Principles of Catalyzation & Application 大电流测量Super-Current Measurement 大电源测量Super-Power MeasurementShip Structure GraphingShip VibrationCreativity PsychologyMagnetic Measurement Technology大机组协调控制 Coordination & Control of Generator Networks 大跨度房屋结构 Large-Span House structure 大型锅炉概况 Introduction to Large-V olume Boilers 大型火电机组控制Control of Large Thermal Power Generator Networks 大学德语 大学俄语 大学法语 大学日语 大学英语 大学语文 大众传播学 代用运放电路 Simulated Transmittal Circuit 单片机原理Fundamentals of Mono-Chip Computers 单片机原理及应用Fundamentals of Mono-Chip Computers & Applications 弹性力学 Theory of Elastic Mechanics 当代国际关系 Contemporary International Relationship 当代国外社会思维评价 Evaluation of Contemporary Foreign SocialThought 当代文学 Contemporary Literature 当代文学专题 Topics on Contemporary Literature 当代西方哲学 Contemporary WesternPhilosophy当代戏剧与电影 Contemporary Drama & Films 党史 History of the Party 导波光学 Wave Guiding Optics 等离子体工程 Plasma Engineering 低频电子线路 Low Frequency Electric Circuit 低温传热学 Cryo Conduction 低温固体物理 Cryo Solid Physics 低温技术原理与装置 Fundamentals of Cryo Technology &Equipment 低温技术中的微机原理 Priciples of Microcomputer in Cryo Technology 低温绝热 Cryo Heat Insulation 低温气体制冷机 Cryo Gas Refrigerator 低温热管 Cryo Heat Tube 低温设备 Cryo Equipment 低温生物冻干技术 Biological Cryo Freezing Drying Technology 低温实验技术 低温物理导论 低温物理概论 低温物理概念 低温仪表及测试 Cryo Meters & Measurement 低温原理 Cryo Fundamentals 低温中的微机应用 Application of Microcomputer in CryoTechnology 低温装置 Cryo Equipment 低噪声电子电路 Low-Noise Electric Circuit 低噪声电子设计 Low-Noise Electronic DesigningCollege German College Russian College FrenchCollege Japanese College English College Chinese Mass Media Cryo Experimentation TechnologyCryo Physic ConceptsCryo Physic ConceptsCryo Physic ConceptsLow-Noise Increasing & Decreasing Detection of Low Noise & Weak Signals History of World War II 电测量技术 Electric Measurement Technology电厂计算机控制系统 Computer Control System in Power Plants 电磁测量实验技术 Electromagnetic Measurement Experiment & Technology 电磁场计算机Electromagnetic Field Computers 电磁场理论 Theory of Electromagnetic Fields 电磁场数值计算 Numerical Calculation of Electromagnetic Fields 电磁场与电磁波 Electromagnetic Fields & Magnetic Waves 电磁场与微波技术 Electromagnetic Fields & Micro-Wave Technology 电磁场中的数值方法 Numerical Methods in Electromagnetic Fields 电磁场中的数值计算 NumericalCalculation in Electromagnetic Fields 电磁学 Electromagnetics 电动力学 Electrodynamics 电镀 Plating 电分析化学 Electro-Analytical Chemistry 电工测试技术基础 Testing Technology of Electrical Engineering 电工产品学 Electrotechnical Products 电工电子技术基础 ElectricalTechnology & Electrical Engineering 电工电子学 Electronics in Electrical Engineering 电工基础 Fundamental Theory of Electrical Engineering 电工基础理论 Fundamental Theory of Electrical Engineering 电工基础实验 Basic Experiment in Electrical Engineering 电工技术Electrotechnics 电工技术基础 Fundamentals of Electrotechnics 电工实习 ElectricalEngineering Practice 电工实验技术基础 Experiment Technology of Electrical Engineering 电工学 Electrical Engineering 电工与电机控制 Electrical Engineering & Motor Control 电弧电接触 Electrical Arc Contact 电弧焊及电渣焊 Electric Arc Welding & Electroslag Welding 电化学测试技术 Electrochemical Measurement Technology 电化学工程 Electrochemical Engineering 电化学工艺学 Electrochemical Technology 电机测试技术 Motor Measuring Technology 电机电磁场的分析与计算 Analysis & Calculation of Electrical Motor & Electromagnetic Fields 电机电器与供电 Motor Elements and Power Supply 电机课程设计 Course Exercise in Electric Engine 电机绕组理论 Theory of Motor Winding 电机绕组理论及应用 Theory &Application of Motor Winding 电机设计 Design of Electrical Motor低噪声放大与弱检低噪声与弱信号检测地理 Geography 第二次世界大战史电机瞬变过程 Electrical Motor Change Processes 电机学 Electrical Motor 电机学及控制电机 Electrical Machinery Control & Technology 电机与拖动 Electrical Machinery & Towage 电机原理 Principle of Electric Engine 电机原理与拖动 Principles of Electrical Machinery & Towage 电机专题 Lectures on Electric Engine 电接触与电弧 Electrical Contact & Electrical Arc 电介质物理 Dielectric Physics 电镜 Electronic Speculum 电力电子电路电力电子电器 Power Electronic Equipment 电力电子器件 电力电子学 电力工程 Electrical Power Engineering 电力生产技术Technology of Electrical Power Generation 电力生产优化管理 Optimal Management ofElectrical Power Generation 电力拖动基础 Fundamentals for Electrical Towage 电力拖动控制系统 Electrical Towage Control Systems 电力系统 Power Systems 电力系统电源最优化规划 Optimal Planning of Power Source in a Power System电力系统短路 Power System Shortcuts 电力系统分析 Power System Analysis 电力系统规划 Power System Planning 电力系统过电压 Hyper-V oltage of Power Systems 电力系统继电保护原理 Power System Relay Protection 电力系统经济分析 Economical Analysis of PowerSystems 电力系统经济运行 Economical Operation of Power Systems 电力系统可靠性 Power System Reliability 电力系统可靠性分析 Power System Reliability Analysis 电力系统无功补偿及应用 Non-Work Compensation in Power Systems & Applicati电力系统谐波 Harmonious Waves in Power Systems 电力系统优化技术 Optimal Technology of Power Systems 电力系统优化设计 Optimal Designing of Power Systems 电力系统远动Operation of Electric Systems 电力系统远动技术 Operation Technique of Electric Systems 电力系统运行 Operation of Electric Systems 电力系统自动化 Automation of Electric Systems 电力系统自动装置 Power System Automation Equipment 电路测试技术 Circuit Measurement Technology 电路测试技术基础 Fundamentals of Circuit Measurement Technology 电路测试技术及实验 Circuit Measurement Technology & Experiments 电路分析基础 Basis of Circuit Analysis 电路分析基础实验 Basic Experiment on Circuit Analysis电路分析实验 Experiment on Circuit Analysis 电路和电子技术 Circuit and Electronic Technique 电路理论 Theory of Circuit电路理论基础 Fundamental Theory of Circuit 电路理论实验 Experiments in Theory of Circuct 电路设计与测试技术 Circuit Designing & Measurement Technology 电器学 ElectricalAppliances 电器与控制 Electrical Appliances & Control 电气控制技术 Electrical ControlTechnology 电视接收技术 Television Reception Technology 电视节目 Television Porgrams 电视节目制作 Television Porgram Designing 电视新技术 New Television Technology 电视原理 Principles of Television 电网调度自动化 Automation of Electric Network Management 电影艺术 Art of Film Making 电站微机检测控制 Computerized Measurement & Control of Power Statio 电子材料与元件测试技术 Measuring Technology of Electronic Material and Element电子材料元件 Electronic Material and Element 电子材料元件测量 Electronic Material and Element Measurement 电子测量与实验技术 Technology of Electronic Measurement &Experiment 电子测试 Electronic Testing电子测试技术 Electronic Testing Technology 电子测试技术与实验 Electronic TestingTechnology & Experiment 电子机械运动控制技术 Technology of Electronic MechanicPower Electronic CircuitPower Electronic DevicesPower ElectronicsMovement Control 电子技术Technology of Electronics 电子技术腐蚀测试中的应用Application of Electronic Technology in Erosion Measure ment电子技术基础Basic Electronic Technology 电子技术基础与实验Basic Electronic Technology & Experiment 电子技术课程设计Course Exercise in Electronic Technology 电子技术实验Experiment in Electronic Technology 电子理论实验Experiment in Electronic Theory 电子显微分析Electronic Micro-Analysis 电子显微镜Electronic Microscope 电子线路Electronic Circuit 电子线路设计与测试技术Electronic Circuit Design & Measurement Technology电子线路实验Experiment in Electronic Circuit 电子照相技术Electronic Photographing Technology 雕塑艺术欣赏Appreciation of Sculptural Art 调节装置Regulation Equipment 动态规划Dynamic Programming 动态无损检测Dynamic Non-Destruction Measurement 动态信号分析与仪器Dynamic Signal Analysis & Apparatus锻压工艺 Forging Technology 锻压机械液压传动 Hydraulic Transmission in Forging Machinery锻压加热设备 Forging Heating Equipment 锻压设备专题 Lectures on Forging Press Equipments锻压系统动力学 Dynamics of Forging System 锻造工艺 Forging Technology 断裂力学 FractureMechanics 对外贸易概论 Introduction to International Trade 多层网络方法 Multi-Layer NetworkTechnology 多目标优化方法 Multipurpose Optimal Method 多项距阵 Multi-Nominal Matrix 多元统计分析 Multi-Variate Statistical Analysis 发电厂 Power Plant 发电厂电气部分 法律基础 法学概论 法学基础非线性采样系统 Non-Linear Sampling System 非线性光学 非线性规划 非线性振荡 非线性振动 沸腾燃烧 BoilingCombustion 分析化学AnalyticalChemistry分析化学实验 Analytical Chemistry Experiment 分析力学 Analytical Mechanics 风机调节 Fan Regulation 风机调节 .使用 .运转 Regulation,Application & Operation of Fans 风机三元流动理论与设计 Tri-Variate Movement Theory & Design of Fans 风能利用 Wind Power Utilization 腐蚀电化学实验Experiment in Erosive Electrochemistry 复变函数 Complex Variables Functions 复变函数与积分变换 Functions of Complex Variables & Integral Transformation 复合材料力学 CompoundMaterial Mechanics 傅里叶光学 Fourier Optics 概率论 Probability Theory 概率论与数理统计Probability Theory & Mathematical Statistics 概率论与随机过程 Probability Theory & StochasticProcess Electric Elements of Power Plants Fundamentals of LawAn Introduction to Science of LawFundamentals of Science of Law 翻译Translation 翻译理论与技巧 Theory & Skills ofTranslation 泛函分析 Functional Analysis 房屋建筑学 Architectural Design & Construction 非电量测量 Non-Electricity Measurement 非金属材料Non-Metal MaterialsNon-Linear OpticsNon-Linear Programming Non-Linear OcsillationNon-Linear Vibration钢笔画 Pen Drawing 钢的热处理 Heat-Treatment of Steel 钢结构 Steel Structure 钢筋混凝土Reinforced Concrete 钢筋混凝土及砖石结构 Reinforced Concrete & Brick Structure 钢砼结构Reinforced Concrete Structure 高层建筑基础设计 Designing bases of High Rising Buildings 高层建筑结构设计 Designing Structures of High Rising Buildings 高等材料力学 AdvancedMaterial Mechanics 高等代数 Advanced Algebra 高等教育管理 Higher Education Management高等教育史 History of Higher Education 高等教育学 Higher Education 高等数学 AdvancedMathematics 高电压技术 High-V oltage Technology 高电压测试技术 High-V oltage TestTechnology 高分子材料 High Polymer Material 高分子材料及加工 High Polymer Material &Porcessing 高分子化学 High Polymer Chemistry 高分子化学实验 High Polymer ChemistryExperiment 高分子物理 High Polymer Physics 高分子物理实验 High Polymer PhysicsExperiment 高级英语听说 Advanced English Listening & Speaking 高能密束焊 High Energy-Dense Beam Welding 高频电路 High-Frenquency Circuit 高频电子技术 高频电子线路 高压测量技术 高压测试技术高压电场的数值计算 高压电器 High-Voltage Electrical Appliances 高压绝缘 High-VoltageInsulation 高压实验 High-Voltage Experimentation 高压试验技术 High-V oltageExperimentation Technology 工程材料的力学性能测试 Mechanic Testing of EngineeringMaterials工程材料及热处理 Engineering Material and Heat Treatment 工程材料学 EngineeringMaterials 工程测量 Engineering Surveying 工程测试技术 Engineering Testing Technique 工程测试实验 Experiment on Engineering Testing 工程测试信息 Information of Engineering Testing工程动力学 Engineering Dynamics 工程概论 Introduction to Engineering 工程概预算 ProjectBudget工程经济学 Engineering Economics 工程静力学 Engineering Statics 工程力学 EngineeringMechanics 工程热力学 Engineering Thermodynamics 工程项目评估 Engineering ProjectEvaluation 工程优化方法 Engineering Optimizational Method 工程运动学 EngineeringKinematics 工程造价管理Engineering Cost Management 工程制图 Graphingof Engineering 工业分析 Industrial AnalysisIndustrial Boiler工业会计学 Industrial Accounting 工业机器人 Industrial Robot 工业技术基础 BasicIndustrial Technology 工业建筑设计原理 Principles of Industrial Building Design 工业经济理论Industrial Economic Theory 工业经济学 Industrial Economics 工业企业财务管理 IndustrialEnterprise Financial Management 工业企业财务会计 Accounting in Industrial Enterprises 工业企业管理 Industrial Enterprise Management 工业企业经营管理 Industrial EnterpriseAdminstrative Management 工业社会学 Industrial Sociology 工业心理学 Industrial Psychology工业窑炉 Industrial Stoves 工艺过程自动化 Technics Process Automation 公差 CommonDifference 公差技术测量 Technical Measurement with Common Difference 公差与配合Common Difference & Cooperation 公共关系学 Public Relations 公文写作 Document Writing古代汉语 Ancient Chinese 古典文学作品选读 Selected Readings in Classical Literature 固体激光 Solid State Laser 固体激光器件 Solid Laser Elements 固体激光与电源 Solid State Laser &High-Frenquency Electronic Technology High-FrenquencyElectronic Circuit High-V oltage Measurement Technology High-V oltage Testing TechnologyNumerical Calculation in High-V oltage Electronic Field 工业锅炉Power Unit 固体物理Solid State Physics 管理概论Introduction to Management 管理经济学Management Economics 管理数学Management Mathematics 管理系统模拟Management System Simulation 管理心理学Management Psychology 管理信息系统Management Information Systems 光波导理论Light Wave Guide Theory 光电技术Photoelectric Technology 光电信号处理Photoelectric Signal Processing 光电信号与系统分析Photoelectric Signal & Systematic Analysis 光辐射探测技术Ray Radiation Detection Technology 光谱Spectrum 光谱分析Spectral Analysis 光谱学Spectroscopy 光纤传感Fibre Optical Sensors 光纤传感器Fibre Optical Sensors 光纤传感器基础Fundamentals of Fibre Optical Sensors 光纤传感器及应用Fibre Optical Sensors & Applications 光纤光学课程设计Course Design of Fibre Optical 光纤技术实验Experiments in Fibre Optical Technology 光纤通信基础Basis of Fibre Optical Communication 光学Optics 光学测量Optical Measurement 光学分析法Optical Analysis Method 光学计量仪器设计Optical Instrument Gauge Designing 光学检测Optical Detection 光学设计Optical Design 光学信息导论Introduction of Optical Infomation 光学仪器设计Optical Instrument Designing 光学仪器与计量仪器设计Optical Instrument & Gauge Instrument Designing光学仪器装配与校正Optical Instrument Installation & Adjustment 广播编辑学Broadcast Editing 广播新闻Broadcast Journalism广播新闻采写Broadcast Journalism Collection & Composition 广告学Advertisement锅炉燃烧理论Theory of Boiler Combustion 锅炉热交换传热强化Boiler HeatExchange,Condction & Intensification 锅炉原理Principles of Boiler 国际金融International Finance 国际经济法International Economic Law 国际贸易International Trade国际贸易地理International Trade Geography 国际贸易实务International Trade Affairs 国际市场学International Marketing 国际市场营销International Marketing 国民经济计划National Economical Planning 国外社会学理论Overseas Theories of Sociology 过程(控制) 调节装置Process(Control) Adjustment Device 过程调节系统Process Adjustment System 过程控制Process Control 过程控制系统Process Control System 海洋测量Ocean Surveying海洋工程概论Introduction to Ocean Engineering 函数分析Functional Analysis 焊接方法Welding Method 焊接方法及设备Welding Method & Equipment 焊接检验Welding Testing 焊接结构Welding Structure 焊接金相Welding Fractography 焊接金相分析Welding Fractography Analysis 焊接冶金Welding Metallurgy 焊接原理Fundamentals of Welding 焊接原理及工艺Fundamentals of Welding & Technology 焊接自动化Automation of Welding 汉语Chinese 汉语与写作Chinese & Composition 汉语语法研究Research on Chinese Grammar 汉字信息处理技术Technology of Chinese Information Processing 毫微秒脉冲技术Millimicrosecond Pusle Technique 核动力技术Nuclear Power Technology 合唱与指挥Chorus & Conduction 合金钢Alloy Steel 宏观经济学Macro-Economics 宏微观经济学Macro Micro Economics 红外CCD Infrared CCD 红外电荷耦合器Infrared Electric Charge Coupler 红外探测器Infrared Detectors 红外物理Infrared Physics 红外物理与技术Infrared Physics & Technology 红外系统Infrared System 红外系统电信号处理Processing Electric Signals from Infrared Systems 厚薄膜集成电路Thick & Thin Film Integrated Circuit 弧焊电源Arc Welding Power 弧焊原理Arc Welding Principles 互换性技术测量基础Basic Technology of Exchangeability Measurement 互换性技术测量Technology of Exchangeability Measurement 互换性与技术测量Elementary Technology of Exchangeability Measurement 互换性与技术测量实验Experiment of Exchangeability Measurement Technology 画法几何及机械制图Descriptive Geometry & Mechanical Graphing 画法几何与阴影透视DescriptiveGeometry,Shadow and Perspective 化工基础Elementary Chemical Industry 化工仪表与自动化Chemical Meters & Automation 化工原理Principles of Chemical Industry 化学Chemistry 化学反应工程Chemical Reaction Engineering 化学分离Chemical Decomposition化学工程基础Elementary Chemical Engineering 化学计量学Chemical Measurement 化学文献Chemical Literature 化学文献及查阅方法Chemical Literature & Consulting Method 化学粘结剂Chemical Felter 环境保护理论基础Basic Theory of Environmental Protection 环境化学Environomental Chemistry 环境行为概论Introduction to Environmental Behavior 换热器Thermal Transducer 回旧分析与试验设计Tempering Analysis and Experiment Design 回转式压缩机Rotary Compressor 回转压缩机数学模型Mathematical Modeling of Rotary Compressors 会计学Accountancy 会计与财务分析Accountancy & Financial Analysis 会计与设备分析Accountancy & Equipment Analysis 会计原理及外贸会计Principles of Accountancy & Foreign Trade Accountancy 会计原理与工业会计Principles of Accountancy & Industrial Accountancy 活力学Energy Theory 活塞膨胀机Piston Expander 活塞式制冷压缩机Piston Refrigerant Compreessor 活塞式压缩机Piston Compressor 活塞式压缩机基础设计Basic Design of Piston Compressor 活塞压缩机结构强度Structural Intensity of Piston Compressor 活赛压机气流脉动Gas Pulsation of Piston Pressor 货币银行学Currency Banking 基本电路理论Basis Theory of Circuit 基础写作Fundamental Course of Composition 机床电路机床电器Machine Tool Electric Appliance 机床电气控制Electrical Control of Machinery Tools 机床动力学Machine Tool Dynamics 机床设计Machine Tool design 机床数字控制Digital Control of Machine Tool 机床液压传动Machinery Tool Hydraulic Transmission 机电传动Mechanical & Electrical Transmission 机电传动控制Mechanical & electrical Transmission Control 机电耦合系统Mechanical & Electrical Combination System 机电系统计算机仿真Computer Simulation of Mechanic/Electrical Systems 机电一体化Mechanical & Electrical Integration 机构学Structuring 机器人Robot 机器人控制技术Robot Control Technology 机械产品学Mechanic Products 机械产品造型设计Shape Design of Mechanical ProductsMachine Tool Circuit机械工程控制基础 Basic Mechanic Engineering Control 机械加工自动化 Automation inMechanical Working 机械可靠性 Mechanical Reliability 机械零件 Mechanical Elements 机械零件设计 Course Exercise in Machinery Elements Design 机械零件设计基础 Basis of MachineryElements Design 机械设计 Mechanical Designing 机械设计基础 Basis of MechanicalDesigning 机械设计课程设计 Course Exercise in Mechanical Design 机械设计原理 Principle ofMechanical Designing 机械式信息传输机构 Mechanical Information Transmission Device 机械原理 Principle of Mechanics 机械原理和机械零件 Mechanism & Machinery 机械原理及机械设计 Mechanical Designing 机械原理及应用 Mechanical Principle & Mechanical Applications 机械原理课程设计 Course Exercise of Mechanical Principle 机械原理与机械零件 MechanicalPrinciple and Mechanical Elements 机械原理与机械设计 Mechanical Principle and MechanicalDesign 机械噪声控制 Control of Mechanical Noise 机械制造概论 Introduction to MechanicalManufacture 机械制造工艺学 Technology of Mechanical Manufacture 机械制造基础Fundamental of Mechanical Manufacture 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高等数学国外经典教材目录

高等数学国外经典教材目录

高等数学国外经典教材目录IntroductionIn the field of higher mathematics, numerous classic textbooks from around the world have greatly contributed to the understanding and development of advanced mathematical concepts. This article aims to provide a comprehensive catalog of some of the most influential and well-regarded international textbooks on advanced mathematics.1. "Advanced Engineering Mathematics" by Erwin KreyszigThis widely acclaimed textbook covers a broad range of topics in advanced mathematics, making it a valuable resource for engineering and mathematics students alike. Its comprehensive approach combines theory, examples, and applications, ensuring a thorough understanding of the subject matter. Topics covered include vector calculus, complex analysis, differential equations, Fourier analysis, and more.2. "Principles of Mathematical Analysis" by Walter RudinConsidered a classic in the field, this rigorous textbook introduces students to real and complex analysis. Through clear and concise explanations, Rudin presents foundational topics such as sequences, continuity, differentiation, and integration. With challenging exercises and proof-based explanations, this book serves as an essential reference for those seeking a deeper understanding of mathematical analysis.3. "Linear Algebra and Its Applications" by Gilbert StrangStrang's textbook offers a comprehensive introduction to linear algebra, a fundamental branch of mathematics. The book covers topics such as vector spaces, matrix operations, determinants, eigenvalues, and eigenvectors. Strang's approach emphasizes applications, making it a valuable resource for students in various fields, including engineering, computer science, and physics.4. "Probability and Statistics" by Morris H. DeGroot and Mark J. SchervishThis textbook provides a thorough introduction to the principles and applications of probability and statistics. It covers topics such as probability theory, random variables, expectation, estimation, hypothesis testing, and regression analysis. With clear explanations and numerous examples, this book is widely used in both undergraduate and graduate courses.5. "Differential Equations and Their Applications" by Martin BraunBraun's textbook offers a comprehensive introduction to ordinary differential equations and their applications. It provides a solid foundation in the theory of differential equations and explores various applications in physics, engineering, and biology. The book covers topics such as first-order equations, linear equations, systems of equations, Laplace transforms, and numerical methods for solving differential equations.6. "Complex Analysis" by Joseph Bak and Donald J. NewmanThis textbook provides a clear and thorough introduction to complex analysis, an area of mathematics that deals with functions of complex variables. Bak and Newman present the theory of complex variables and itsapplications in an accessible manner. Topics covered include analytic functions, Cauchy's theorem, residues, conformal mapping, and harmonic functions.ConclusionThese are just a few examples of the many outstanding advanced mathematics textbooks available internationally. Each of these books offers a unique perspective and approach to the subject matter, providing valuable insights and knowledge to students and researchers in the field of higher mathematics. By studying these classic texts, individuals can deepen their understanding and appreciation for the beauty and complexity of advanced mathematical concepts.。

线性方程式

线性方程式
1.4
? Ex 2: Parametric representation (參數化表示) of a solution set
x1 ? 2x2 ? 4 with a solution (2, 1), i.e., x1 ? 2, x2 ? 1
※ If you solve for x1 in terms of x2, you obtain x1 ? 4 ? 2x2 (in this form, the variable x2 is free)
? Notes: Each of the following operations on a system of linear equations produces an equivalent system
O1: Interchange two equations O2: Multiply an equation by a nonzero constant O3: Add a multiple of an equation to another equation
Chapter 1 Systems of Linear Equations
1.1 Introduction to Systems of Linear Equations 1.2 Gaussian Elimination and Gauss-Jordan Elimination 1.3 Applications of Systems of Linear Equations
1.7
? Ex 4: Solution of a system of linear equations in 2 variables
(1) x ? y ? 3 x ? y ? ?1 two intersecting lines

Systems of Linear Equations 4

Systems of Linear Equations 4

Systems of Linear Equations 4In this chapter direct methods for solving systems of linear equations A x =b. 11111.n n nn a a b A b a a bn ⎡⎤⎡⎤⎢⎥⎢⎥==⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦Will be presented.Here A is given n n ⨯ matrix. And b is a given vector. We assume in additionthat A and b are teal. Althougn this restriction is inessen. Tial in most of the methods. In contrast to the iterative methods(Chatpte 8), the direct methods discussed here produce the solution in finitely many steps. Assuming computations without roundoff errors.This problem is closely related to that of computing the inverse 1A - of the matrix A provided this inverse exists. For if 1A - is known,the solution x of Ax=b can be obtained by matrix vector multiplication, x =1A -b.Conversely. the i th column i a of 1A -=(1,n a a ) is the solution of the linear system i Ax e =,where i e =T (0,,0,1,0,,0) is the i th unit vector.A general introduction to numerical linear algebra is given in Golub and van Loan(1983) and Stewart(1973). ALGOL programs are found in Wilkinson and Reinsch(1971), FORTRAN programs in Dongarra, Bunch,Moler, and stewart(1979)(LINPACH), and in Andersen et al.(1992)(LAPACK).4.1 Gaussian Elimination. The Triangular Decomposition of a Matrix In the method of Gaussian elimination for solving a system of linear equations (4.1.1) ,Ax b =Where A is an n n ⨯ matrix and n b R ∈. The given system (4.1.1) is transformed in steps by appropriate rearrangements and linear combinations of equations into a system of the form R x c =, 1110n nn r r R r ⎡⎤⎢⎥=⎢⎥⎢⎥⎣⎦Which has the same solution as (4.1.1). R is an upper triangular matrix. So that R x c = can easily be solved by “back substitution ”(so long as 0,1,,ii r i n ≠= ):1ni ik kk i i iic r x x r =+-=∑ for ,1,,1i n n =- .In the first step of the algorithm an appropriate multiple of the first equation is subtracted from all of the other equations in such a way that the coefficients of 1x vanish in these equations: hence.1x remains only in the first equation. This is possible only if 110a ≠. Of course, which can beachieved by rearranging the equations if necessary. As long as at least one 10i a =. Instead ofworking with the equations themaselves. The operations are carried out on the matrix ()11111,n n nnn a a b A b a a b ⎡⎤⎢⎥=⎢⎥⎢⎥⎣⎦Which corresponds to the full system given in (4.1.1) The first step of the Gaussian elimination process leads to a matrix (),A b ''of the form (4.1.2) ()111211222220,0n n nnnna a ab a a b A b a a b ''''⎡⎤⎢⎥'''⎢⎥''=⎢⎥⎢⎥'''⎣⎦, And this step can be described formally as follows: (4.1.3)(a) Determine an element 10r a ≠ and proceed with (b); if no such r exists, A is singular; set()(),,A b A b ''=; stop.(b) Interchange rows r and 1 of (),A b . The result is the matrix (,)A b . (c) For 2,3,,i n = , subtract the multiple 1111/i i l a a =Of row 1 from row i of the matrix (),A b . The desired matrix (),A b '' is obtained as the result. The transition (,)(,)(,)A b A b A b ''−−→−−→ can be described by using matrixmultiplications:(4.1.4) 1(,)(,)A b P A b =, 111(,)(,)(,)A b G A b G P A b ''==. Where 1P is a permutation matrix. And 1G is a lower triangular matrix:(4.1.5) 101011101101P r ⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥=⎢⎥←−−⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦. 21111011n l G l ⎡⎤⎢⎥-⎢⎥=⎢⎥⎢⎥-⎣⎦Matrices such as 1G , which differ in at most one column from an identity matrix, are called Frobenius matrices . Both matrices 1P and 1G are nonsingular; in fact111P P -=. 211111011n l G l -⎡⎤⎢⎥⎢⎥=⎢⎥⎢⎥⎣⎦For this reason, the equation systems A x b = and A x b ''= have the same solution: A x b = implies1111G P Ax A x b G P b''===, and A x b ''= implies11111111P G A x Ax b P G b ----''===.The element 111r a a = which is determined in (a) is called the pivot element (or simply the pivot ). And step (a) itself is called pivot selection (or pivoting ). In the pivot selection one can. In theory, choose any 10r a ≠ be chosen. Usually the choice 11max r i ia a =Is made: that is, among all candidate elements the one of largest absolute value is selected. (It is assumed in making this choice however---see Section 4.5---that the matrix A is “equilibrated ”, that is. That the orders of magnitudes of the elements of A are “roughly equal ”.)This sort of pivot selection is called partial pivot selection (or complete pivoting), in which the search for a pivot is not restricted to the first column; that is, (a) and (b) in (4.1.3) are replaced by (a ') and (b '): (a ')Determine r and s so that,m ax rs ij i ja a =and continue with (b ') if 0rs a ≠. Otherwise A is singular; set ()(),,A b A b ''=; stop. (b ')Interchange rows 1 and r of (),A b , as well as columns 1 and s. Let the resulting matrix be(),A b .After the first elimination step, the resulting matrix has the form (4.1.2): () 111,0Ta ab A b Ab '''⎡⎤''=⎢⎥⎢⎥⎣⎦with an (1)n --row matrix A . The next elimination step consists simply of applying the processdescribed in (4.1.3) for (,)A b to the smaller matrix(,)A b . Carrying on in this fashion. A sequence of matrices(0)(0)(1)(1)(1)(1)(,)(,)(,)(,)(,)n n A b AbAbAbR c --=−−→−−→−−→=is obtained which begins with the given matrix (,)A b (4.1.1) and ends with the desired matrix(,)R c . In this sequence the j th intermediate matrix ()()(,)j j Abhas the form(4.1.6) ()()()()()11121()()222******0*(,)0****000***00***j j j j j j j A A b A b A b ⎡⎤⎢⎥⎢⎥⎢⎥⎡⎤⎢⎥⎢⎥==⎢⎥⎢⎥⎢⎥⎣⎦⎢⎥⎢⎥⎢⎥⎣⎦with a j -row upper triangular matrix ()11j A . The transition ()()(1)(1)(,)(,)j j j j A b A b ++−−→consists of the application of (4.1.3) on the (1)(1)n n j -⨯-+ matrix ()()222(,)j j A b . Theelements of ()11j A ,()12j A ,()1j b do not change from this step on; hence they agree with thecorresponding elements of (,)R c . As in the first step, (4.1.4) and (4.1.5), the ensuing steps can be described using matrix multiplication. As can be readily seen (4.1.7) ()()(1)(1)(,)(,)j j j j j j AbG P Ab--=,112211(,)(,)n n n n R c G P G P G P A b ----= . with permutation matrices j P and nonsingular Frobenius matrices j G of the form(4.1.8) 1,,10111j j jn jG l l +⎡⎤⎢⎥⎢⎥⎢⎥=⎢⎥-⎢⎥⎢⎥⎢⎥-⎢⎥⎣⎦in the j th elimination step (1)(1)()()(,)(,)j j j j A bAb--−−→ the elements below the diagonalin the j th column are anihilated. In the implementation of this algorithm on a computer, the locations which were occupied by these elements can now be used for the storage of the important quantities ,i j l ,1i j ≥+, of j G ; that is, we work with a matrix of the form111211,111212223132(),1,()()()1,1,11,1()()()2121,,1,j j n j j jjj j j n j j j j j jj j j nj j j j n jn j n nn r r r r r c r r r r r c Ta ab a a b λλλλλλλ++++++++⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥=⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦Here the subdiagonal elements 1,2,,,,k k k k nk λλλ++ of the k th column are a certain permutation of the elements 1,,,k k n k l l + of k G in (4.1.8).Based on this arrangement. The j th step (1)()j j T T -−−→,1,2,,1j n =- . Can be describedas follows (for simpicity the elements of (1)j T - are denoted by ik t , and those of ()j T byikt ',1,11i n k n ≤≤≤≤+) : (a) Partial pivot selection: Determine r so thatm ax ij ij i jt t ≥=.If 0ij t =, set ()(1)j j T T -=; A is singular; stop. Otherwise carry on with (b). (b) Interchange rows r and j of (1)j T -, and denote the result by ()ik T t =. (c) Replace/ij jj ijij t l t t '== for 1,2,,i j j n =++ , ik jk ikij t t l t '=- for 1,,i j n =+ and 1,,1k j n =++ . ik ikt t '= otherwise. We note that in (c) the important elements 1,,,j j nj l l + of j G are stored in their natural orderas 1,,j j njt t +'' . This order may, however, be changed in the subsequent elimination steps ()(1)k k TT+−−→,k j ≥, because in (b) the rows of the entire matrix ()k T are rearranged. Thishas the following effect: The lower triangular matrix L and the upper triangular matrix R .211,1101n n n t L t t -⎡⎤⎢⎥⎢⎥=⎢⎥⎢⎥⎣⎦, 1110n nn t t R t ⎡⎤⎢⎥=⎢⎥⎢⎥⎣⎦, which are contained in the final matrix (1)()n ik T t -=, provide a triangular decomposition of the matrix P A :(4.1.9) LR PA =.In this decomposition P is the product of all of the permutations appearing in (4.1.7):121n n P P P P --= .We will only show here that a triangular decomposition is produced if no row interchanges are necessary during the course of the elimination process, i.e., if 11n P P P I -==== . In this case, 211,1101n n n l L l l -⎡⎤⎢⎥⎢⎥=⎢⎥⎢⎥⎣⎦, since in all of the minor steps (b) nothing is interchanged. Now, because of(4.1.7), 11n R G G A -= ; therefore(4.1.10) 1111n G G R A ---= .since11,1011jj j njGl l -+⎡⎤⎢⎥⎢⎥⎢⎥=⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦, it is easily verified that211111,1101jn n n n l GGL l l ----⎡⎤⎢⎥⎢⎥==⎢⎥⎢⎥⎣⎦. Then the assertion follows from (4.1.10).X A M P LEE.123316221371114x x x ⎡⎤⎡⎤⎡⎤⎢⎥⎢⎥⎢⎥=⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦⎣⎦. 316231623162211711210213713333331114111021114333322⎡⎤⎡⎤⎢⎥⎢⎥⎢⎥⎡⎤⎢⎥⎢⎥⎢⎥-→→-⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎢⎥⎢⎥-⎢⎥-⎣⎦⎢⎥⎣⎦. The pivot elements are marked. The triangular equation system is 1233162210013314002x x x ⎡⎤⎢⎥⎡⎤⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥-=⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎢⎥⎣⎦⎢⎥-⎣⎦. Its solution is18x =- 23310()723x x =+=- 3231(26)193x x x =--=.Further 100001010P ⎡⎤⎢⎥=⎢⎥⎢⎥⎣⎦, 316111213PA ⎡⎤⎢⎥=⎢⎥⎢⎥⎣⎦, and the matrix P A has the triangular decomposition PA LR = with 100110321132L ⎡⎤⎢⎥⎢⎥⎢⎥=⎢⎥⎢⎥⎢⎥⎣⎦, 31620131002R ⎡⎤⎢⎥⎢⎥⎢⎥=-⎢⎥⎢⎥⎢⎥-⎣⎦. Triangular decompositions (4.1.9) are of great practical importance in solving systems of linear equations. If the decomposition (4.1.9) is known for a matrix A (that is, the matrices L ,R ,P are known), then the equation system A x b =can be solved immediately with any right-hand side b; for it follows thatP A x L R x P b ==,from which x can be found by solving both of the triangular systemsL u P b =, R x u =(provided all 0ii r ≠).Thus, with the help of the Gaussian elimination algorithm. It can be shown constructively that each square nonsingular matrix A has a triangular decomposition of the form (4.1.9). however, not every such matrix A has a triangular decomposition in the more narrow sense A LR =, as the example0110A ⎡⎤=⎢⎥⎣⎦shows. In general, the rows of A msust be permuted appropriately at the outset.The triangular decomposition (4.1.9) can be obtained directly without forming the intermediate matrices ()jT . For simplicity, we will show this under the assumption that the rows of A do nothave to be pernuted in order for a triangular decomposition A LR = to exist. The equationsA LR = are regarded as 2n defining equations for the 2n unknown quantitiesik r i k ⋅≤,ik l i k ⋅≥ (1ii l =):that is.(4.1.11) m in(,)1i k ik ij jk j a l r ==∑(1ii l =).The order in which the ij jk l r ⋅ are to be computed remains open. The following versions are common:In the Crout method the n n ⨯ matrix A LR = is partitioned as follows:and the equations A LR = are solved for L and R in an order indicated by this partitioning:(1) 111111i jji i i j a lr r a ==⋅=∑, 1,2,,i n =(2) 111111111/i ijj i i i j a lr l a a r ==⋅==∑, 2,3,,i n =(3) 222222111i jji i i i j a lr r a l r ==⋅=-∑, 2,3,,i n = . Etc.And in general, for 1,2,,i n = .(4.1.12) 11i ik ik ij jk j r a l r -==-∑ ,1,,k i i n=+ . 11i k i k ij ij ki iia l r l r -=-=∑1,2,,k i i n=++ . In all of the steps above 1ii l = for 1,2,,i n = . In the Banachiewicz method, the partitioningis used: that is, L and R are computed by rows.The formulas above are valid only if no pivot selection is carried out. Triangular decomposition by the methods of Crout or Banachiewicz with pivot selection leads to more complicated algorithms: see Wilkinson (1965).Gaussian elimination and direct triangular decomposition differ only in the ordering of operations. Both algorithms are, theoretically and numerically,entirely equ ivalent. Indeed, the j th partial sums(4.1.13) ()1jj ikik is sk s aa l r ==-∑of (4.1.12) produce precisely the elements of the matrix ()j A in (4.1.6). as can easily be verified. In Gaussian elimination, therefore, the scalar products (4.1.12) are formed only in pieces, with temporary storing of the intermediate results: direct triangular decomposition require about 3/3n operations (1 operation =1 multiplication + 1 addition). Thus, they also offer a simple way of evaluating the determinant of a matrix A : From (4.1.9) it follows.sincedet()1P =±,det()1L =, that1122det()det()det()nn PA A R r r r =±== .Up to its sign, det()A is exactly the product of the pivot elements. (It should be noted that the direct evaluation of the formula121112,,1det()(,,)n n i k nn n fori kA sign a a a μμμμμμμμμ====∑requires 3!/3n n operations.)In the case that P I =, the pivot elements ii r are representable as quotients of the determinants of the principal minors of A . If, in the representation LR A =, the matrices are partitioned as follows: 1111121121212222122200L R R A A L L R A A ⎡⎤⎡⎤⎡⎤=⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦⎣⎦, it is found that 111111L R A =: hence 1111det()det()R A =, or1111det()ii r r A = ,where 11A is an i i ⨯ matrix. In general, if i A denotes the i th principal minor of A , then1det()/det()ii i i r A A -=. 2i ≥.111det()r A =.A further practical and important property of the method of triangular decomposition is that, for band matrices with bandwidth m . ******mA m ⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥=⎢⎥⎢⎥⎫⎢⎥⎪⎬⎢⎥⎪⎢⎥⎣⎦⎭. 0ij a = for i j m -≥.the matrices L and R of the decomposition LR PA = of A are not full: R is a band matrix with bandwidth 21m -.***210*R m ⎡⎤⎢⎥⎢⎥⎢⎥=⎫⎪⎢⎥-⎬⎢⎥⎪⎢⎥⎣⎦⎭. and in each column of L there are at most m elements different from zero. In contrast, the inverses 1A - of band matrices are usually filled with nonzero entries.Thus, if m n , using the triangular decomposition of A to solve A x b = results in a considerable saving in computation and storage over using 1A -. Additional savings are possible by making sue of the symmetry of A if A is a positive definite matrix (see Sections 4.3 and 4.A).4.2 The Gauss-Jordan AlgorithmIn practice, the inverse 1A - of a nonsingular n n ⨯ matrix A is not frequently needed. Should a particular situation call for an inverse, however, it may be readily calculated using the triangular decomposition described in Section 4.1 or using the Gauss-Jordan algorithm, which will be described below. Both methods require the same amount of work.If the triangular decomposition PA LR = of (4.1.9) is available, then the i th column i aof1A - is obtained as the solution of the system(4.2.1) i i LR a P e =,where i eis the i th coordinate vector. If the simple structure of the right-hand side of (4.2.1), i P e, is taken into account, then the n equation systems (4.2.1) (1,,i n = ) can be solved inabout323n operations. Adding the cost of producing the decomposition gives a total of 3noperations to determine 1A -. The Gauss-Jordan method requires this amount of work, too, and offers advantages only of an organizational nature. The Gauss-Jordan method is obtained if one attempts to invert the mapping x Ax y →=. ,nnx y ∈∈ determined by A in asystematic manner. Consider the system Ax y =:(4.2.2) 1111111,.n n n nn n n a x a x y a x a x y ++=++=In the first step of the Gauss-Jordan method, the variable 1x is exchanged for one of the variables r y . To do this, an 10r a ≠ is found, for example (partial pivot selection ) 11max r i ia a =,and equations r and 1 of (4.2.2) are interchanged. In this way , a system(4.2.3)1111111,n n n nn n na x a x y a x a x y ++=++=is obtained in which the variables 1,,n y y are a permutation of 1,,n y y and 111r a a =,1r y y = holds. Now,110a ≠, for otherwise we would have 10i a ≠ for all i ,making A singular, contrary to assumption. By solving the first equation of (4.2.3) for 1x and substituting the result into the remaining equations, the system(4.2.4)11122111212222121221,,n n n n nn nn n n a y a x a x x a y a x a x y a y a x a x y '''+++='''+++='''+++=is obtained with(4.2.5)11111111111111111,,,,2,3,,.k k i i k ik i ika a a a a a a a a a a fori k n a a ''==''==-=In the next step, the variable 2x is exchanged for one of the variables 2,,n y y ; then 3x is exchanged for one of the remaining y variables, and so on. If the successive equation systems are represented by their matrices, then starting from (0)A A =, a sequence(0)(1)()n AAA→→is obtained. The matrix ()()()j j ik A a = stands for a “mixed equation system ” of the form(4.2.6)()()()()1111,11111()()()()1,111()()()()111,1,111,11()()()(1,,111,,,j j j j j j j n n j j j j j j jj j j j jn n j j j j j j j j jj j j j nn j j j j j j n n j n j j nn j a y a y a x a x x a y a y a x a x x ay ay a x ax y a y a y a x a ++++++++++++++++++=+++++=+++++=+++++).n n x y =In this system 11(,,,,,)j j n y y y y + is certain permutation of the original variables1(,,)n y y . In the transition (1)()j j AA-→ the variable j x is exchanged for j y . Thus,()j A is obtained from (1)j A - according to the rules given below. For simplicity, the elements of(1)j A- are denoted by ik a , and those of ()j A are denoted by ika '. (4.2.7)(a) Partial pivot selection: Determine r so thatm ax rj ij i ja a ≥=.If 0rj a =, the matrix is singular . Stop.(b) Interchange rows r and j of (1)j A -, and call the result ()ik A a =.(c) Compute ()()j ikA a '= according to the formulas [compare with (4.2.5)] 1/jj jj a a '=,,,jk ij jk ijjjjja a a a fori k j a a ''=-=≠,ij jk ik ikjja a a a a '=-.(4.2.6) implies that (4.2.8) ()1,(,,)n T n Ay x y y y == ,where 1,,n y y is a certain permutation of the original variables 1,,n y y , y Py = which, since it corresponds to the interchange step (4.2.7b), can easily be determined. From (4.2.8) it follows that()()n AP y x =,and therefore, since Ax y =, 1()n AAP -=.X A M P LEE. (0)(1)(2)111111211123112112136125121A AA A --⎡⎤⎡⎤⎡⎤-⎢⎥⎢⎥⎢⎥==→=→=--⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥-⎣⎦⎣⎦⎣⎦(3)1331352121AA --⎡⎤⎢⎥→=--=⎢⎥⎢⎥⎣⎦. The pivot elements are marked.The following ALGOL program is a formulation of the Gauss-Jordan method with partial pivoting. The inverse of the n nmatrix A is stored back into A. The array []p i serves to store the information about the row permutations which take place.for j=1 step 1 until n do p[j]=j;for j=1 step 1 until n dobeginpivotsearch:max=abs(a[j,j]);r=j;for i=j+1 step 1 until n doif abs(a[i,j])greater max thenbegin max=abs(a[i,j]);r=iend;if max=0 then goto singular;rowinterchange:if r>j thenbegin for k=1 step 1 until n dobeginhr=a[j,k];a[j,k]=a[r,k];a[r,k]=hrend;hi=p[j];p[j]=p[r];p[r]=hiend;transformation:hr=1/a[j,j];for i=1 step 1 until n doa[i,j]=hr*a[i,j];a[j,j]=hr;for k=1 step 1 until j-1,j+1 step 1 until n dobeginfor i=1 step 1 until j-1,j+1 step 1 until n doa[i,k]=a[i,k]-a[i,j]*a[j,k];a[j,k]=-hr*a[j,k]end kend j;columninterchange:for i=1 step 1 until n dobeginfor k=1 step 1 until n do hv[p[k]]=a[i,k];for k=1 step 1 until n do a[i,k]=hv[k]end;4.3 The Cholesky DecompositionThe methods discussed so far for solving equations can fail if no pivot selection is carried out, i.e. if we restrict ourselves to taking the diagonal elements in order as pivots. Even if no failure occurs, as we will show in the next sections, pivot selection is advisable in the interest of numerical stability. However, there is an important class of matrices for which no pivot selection is necessary in computing triangular factors: the choice of each diagonal element in order always yields a nonzero pivot element. Furthermore, it is numerically stable to use these pivots. We refer to the class of positive definite matrices.(4.3.1) Definition. A (complex) n n ⨯ matrix A is said to be positive definite if it satisfies: (a) H A A =,i.e.,A is a Hermitian matrix. (b) 0H x Ax > for all ,0n x x ∈≠ .HA A = is called positive semidefinite if 0A x ≥ holds for all n x ∈ .(4.3.2) Theorem. For any positive definite matrix A the matrix 1A - exists and is also positive definite. All principal submatrices of a positive definite matrix are also positive definite, and all principal minors of a positive definite matrix are positive.R O O FP. The inverse of a positive definite matrix A exsits: If this were not the case, an 0x ≠would exist with 0A x = and 0H x Ax =, in contradiction to the definiteness of A . 1A - is positive definite: We have 111()()H H A A A ---==, and if 0y ≠ it follows that10x A y -=≠. Hence 1110HHHy A y x A A Ax x Ax ---==>. Every principal submatrix1111k k k k i i i i i i i i a a A a a ⎡⎤⎢⎥=⎢⎥⎢⎥⎣⎦of a positive definite matrix A is also positive definite: Obviously HA A =. Moreover, every1,0k k xx xx ⎡⎤⎢⎥=∈≠⎢⎥⎢⎥⎣⎦can be expanded to 1,1,,,,0,,jj nn x x fori j k x x x otherw ise x μμ⎡⎤⎧==⎪⎢⎥=∈≠=⎨⎢⎥⎪⎩⎢⎥⎣⎦and it follows that0H H x A xx A x =>. In order to complete the proof of (4.3.2), then, it suffices to show that det()0A > for positivedefinite A . This is shown by using induction on n .For 1n = this is true from (4.3.1b). Now assume that the theorem is true for positive definite matrices of order 1n -, and let A be a positive definite matrix of order n . According to the preceeding parts of the proof,11111n n nn Aαααα-⎡⎤⎢⎥=⎢⎥⎢⎥⎣⎦is positive definite, and consequently 110α>. As is well known,By the induction assumption, however,and hence det()0A > follows from 110α>.(4.3.3) Theorem. For each n n ⨯ positive definite matrix A there is a unique n n ⨯ lower triangular matrix (0)ik L l fork i >> with 0ii l >. 1,2,,i n = . satisfyingHA LL =. If A is real, so is L .(Note that 1ii l = is not required.)R O O FP. The theorem is establishied by induction on n . For 1n = the theorem is trivial: Apositive definite 11⨯ matrix ()A α= is a positive number 0α>, which can be written uniquely in the form1111l l α=, 11l =Assume that the theorem is true for positive definite matrices of order 1n -. An n n ⨯ positive definite matrix A can be partitioned into 1n Hnn A b A ba -⎡⎤=⎢⎥⎣⎦, where 1n b -∈and 1n A - is a positive definite matrix of order 1n - by (4.3.2). By theinduction hypothesis, there is a unique matrix 1n L - of order 1n - satisfying111Hn n n A L L ---=. 0,0ik ii l fo rk i l =>>.We consider a matrix L of the form10n HL L cα-⎡⎤=⎢⎥⎣⎦and try to determine 1,0n c α-∈> so that(4.3.4) 11100Hn n n H Hnn A b L L c A b a cαα---⎡⎤⎡⎤⎡⎤==⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦⎣⎦. This means that we must have1n L c b -=, 2,0Hnn c c a αα+=>.The first equation must have a unique solution 11n c L b --=, since 1n L -, as a triangular matrix with positive diagonal entries, has ()1det 0n L ->. As for the second equation, if H nn c c a ≥(that is,20α≤), then from (4.3.1) we would have a contradiction with 20α>, which follows from221det()det()n A L α-=,det()0A >(4.3.2), and 1det()0n L ->. Therefore, from (4.3.4), there exists exactly one 0α>giving H LL A =, namelyα=. □ The decomposition H A LL = can be determined in a manner simillar to the methods given in Section 4.1. If it is assumed that all ij l are known for 1j k ≤-, then as defining equations forkk L and ,1ik L i k ≥+, we have(4.3.5)222121212,0,.kk k k kkkk k k kk ik i i ik a l l l l a l l l l l l =+++>=+++from H A LL =.For a real A , the following algorithm results: for i=1 step 1 until n do for j=i step 1 until n do begin x=a[i,j]; for k=i-1 step -1 until 1 do x=x-a[j,k]*a[i,k]; if i=j then beginif x<=0 then goto fail; p[i]=1/sqrt(x)end elsea[j,i]=x*p[i]end i,j;Note that only the upper triangular portion of A is used. The lower triangular matrix L is stored in the lower triangular portion of A , with the exception of the diagonal elements of L , whose reciprocals are stored in p .This method is due to Cholesky. During the course of the computation, n square roots must be taken. Theorem (4.3.3) assures us that the arguments of these square roots will be positive. About3/6n operations (multiplications and additons) are needed beyond the n square roots. Furthersubstantial savings are possible for sparse matrices, see Section 4.A. Finally, note as an important implication of (4.3.5) that(4.3.6) 1,,.1,,.kj L j k k n ≤==That is, the elements of L can not grow too large. 4.4 Error BoundsIf any one of the methods described in the previous sections is used to determine the solution of a linear equation system A x b =, then in general only an approximation xto the true solution x is obtained, and there arises the question of how the accuracy of xis judged. In order to measure the error we have to have the means of measuring the “size ” of a vector. To do this, a (4.4.1) :norm xis introduced on n : that is, a function :n⋅→,which assigns to each vector nx ∈ a real value x serving as a measure for the “size ” of x .The function must have the following properties: (4.4.2)(a) 0x > for all nx ∈ ,0x ≠(positivity ),(b) x x αα= for all α∈ ,nx ∈ (homogeneity ),(c) x y x y +≤+ for all ,nx y ∈ (triangle inequality ).In the following we use only the norms(4.4.3) 2(),max(max).iix Euclidian normx x imum norm∞===The norm properties (a),(b),(c) are easily verified.For each norm ⋅the inequality(4.4.4) x y x y-≥-for all ,nx y∈holds. From (4.4.2c) it follows that()x x y y x y y=-+≤-+,and consequently x y x y-≥-. By interchanging the roles of x and y and using (4.4.2b), it follows thatx y y x y x-=-≥-,and hence (4.4.4).It is easy to establish the following:(4.4.5) Theorem. Each norm ⋅on n(or n) is a uniformly continuous function with respectot the metric (,)maxi i ip x y x y=-on n(n).R O O FP. From (4.4.4) it follows thatx h x h+-≤.Now1ni iih h e==∑, where 1(,,)T nh h h= , andie are the usual coordinate (unit) vectors ofn(n). Therefore11m ax m axn ni i i j ii ii jh h e h e M h==≤≤=∑∑with1njjM e==∑. Hence, for each 0ε>and all h satisfying max/i ih Mε≤, the inequalityx h xε+-≤holds. That is, ⋅is uniformly continuous. □This result is used to show:。

线性代数,公开课

线性代数,公开课

22Chapter 1.Introduction to Vectors1.3MatricesThis section is based on two carefully chosen examples.They both start with three vectors.I will take their combinations using matrices .The three vectors in the first example are u ;v ,and w :First example u D 2411035v D 2401 135w D 2400135.Their linear combinations in three-dimensional space are c u C d v C e w :Combinations c 241 1035C d 2401 135C e 2400135D 24cd ce d 35.(1)Now something important:Rewrite that combination using a matrix .The vectors u ;v ;w go into the columns of the matrix A .That matrix “multiplies”a vector:Same combinationis now A times x 24100 1100 113524c d e 35D 24c d c e d 35.(2)The numbers c;d;e are the components of a vector x .The matrix A times the vector x is the same as the combination c u C d v C e w of the three columns:A x D 24u v w 3524cd e 35D c u C d v C e w .(3)This is more than a definition of A x ,because the rewriting brings a crucial change in viewpoint.At first,the numbers c;d;e were multiplying the vectors.Now the matrix is multiplying those numbers.The matrix A acts on the vector x .The result A x is a combination b of the columns of A .To see that action,I will write x 1;x 2;x 3instead of c;d;e .I will write b 1;b 2;b 3for the components of A x .With new letters we seeA x D 24100 1100 113524x 1x 2x 335D 24x 1x 2 x 1x 3 x 235D 24b 1b 2b 335D b .(4)The input is x and the output is b D A x .This A is a “difference matrix ”because b contains differences of the input vector x .The top difference is x 1 x 0D x 1 0.1.3.Matrices23Here is an example to show differences of numbers(squares in x,odd numbers in b):x D2414935D squares A x D241 04 19 435D2413535D b.(5)That pattern would continue for a4by4difference matrix.The next square would be x4D16.The next difference would be x4 x3D16 9D7(this is the next odd number).The matrixfinds all the differences at once.Important Note.You may already have learned about multiplying A x,a matrix times a vector.Probably it was explained differently,using the rows instead of the columns.The usual way takes the dot product of each row with x:Dot products with rows A x D241001100 113524x1x2x335D24.1;0;0/ .x1;x2;x3/. 1;1;0/ .x1;x2;x3/.0; 1;1/ .x1;x2;x3/35:Those dot products are the same x1and x2 x1and x3 x2that we wrote in equation(4). The new way is to work with A x a column at a time.Linear combinations are the key to linear algebra,and the output A x is a linear combination of the columns of A.With numbers,you can multiply A x either way(I admit to using rows).With letters, columns are the good way.Chapter2will repeat these rules of matrix multiplication,and explain the underlying ideas.There we will multiply matrices both ways.Linear Equations One more change in viewpoint is crucial.Up to now,the numbers x1;x2;x3were known (called c;d;e atfirst).The right hand side b was not known.We found that vector of differences by multiplying A x.Now we think of b as known and we look for x.Old question:Compute the linear combination x1u C x2v C x3w tofind b.New question:Which combination of u;v;w produces a particular vector b?This is the inverse problem—tofind the input x that gives the desired output b D A x.You have seen this before,as a system of linear equations for x1;x2;x3.The right hand sides of the equations are b1;b2;b3.We can solve that system tofind x1;x2;x3:x1D b1x1C x2D b2x2C x3D b324Chapter 1.Introduction to VectorsLook at two specific choices 0;0;0and 1;3;5of the right sides b 1;b 2;b 3:b D 2400035gives x D 2400035b D 2413535gives x D 2411C 31C 3C 535D 2414935:The first solution (all zeros)is more important than it looks.In words:If the output is b D 0,then the input must be x D 0.That statement is true for this matrix A .It is not true for all matrices.Our second example will show (for a different matrix C )how we can have C x D 0when C ¤0and x ¤0.This matrix A is “invertible ”.From b we can recover x .The Inverse MatrixLet me repeat the solution x in equation (6).A sum matrix will appear!A x D b is solved by 24x 1x 2x 335D 24b 1b 1C b 2b 1C b 2C b 335D 241001101113524b 1b 2b 335.(7)If the differences of the x ’s are the b ’s,the sums of the b ’s are the x ’s.That was true for the odd numbers b D .1;3;5/and the squares x D .1;4;9/.It is true for all vectors.The sum matrix S in equation (7)is the inverse of the difference matrix A .Example:The differences of x D .1;2;3/are b D .1;1;1/.So b D A x and x D S b :A x D 24100 1100 11352412335D 2411135and S b D 24100110111352411135D 2412335Equation (7)for the solution vector x D .x 1;x 2;x 3/tells us two important facts:1.For every b there is one solution to A x D b .2.A matrix S produces x D S b .The next chapters ask about other equations A x D b .Is there a solution?How is it computed?In linear algebra,the notation for the “inverse matrix”is A 1:A x D b is solved by x D A 1b D S b :Note on calculus .Let me connect these special matrices A and S to calculus.The vector x changes to a function x.t/.The differences A x become the derivative dx=dt D b.t/.In the inverse direction,the sum S b becomes the integral of b.t/.The Fundamental Theorem of Calculus says that integration S is the inverse of differentiation A .Ax D b and x D Sb dx1.3.Matrices 25The derivative of distance traveled .x/is the velocity .b/.The integral of b.t/is the distance x.t/.Instead of adding C C ,I measured the distance from x.0/D 0.In the same way,the differences started at x 0D 0.This zero start makes the pattern complete,when we write x 1 x 0for the first component of A x (we just wrote x 1).Notice another analogy with calculus.The differences of squares 0;1;4;9are odd numbers 1;3;5.The derivative of x.t/D t 2is 2t .A perfect analogy would have produced the even numbers b D 2;4;6at times t D 1;2;3.But differences are not the same as derivatives,and our matrix A produces not 2t but 2t 1(these one-sided “backward differences”are centered at t 12D 2t exactly.(10)Difference matrices are great.Centered is best.Our second example is not invertible .Cyclic DifferencesThis example keeps the same columns u and v but changes w to a new vector w :Second example u D 241 1035v D 2401 135w D 24 10135:Now the linear combinations of u ,v ,w lead to a cyclic difference matrix C :C xD 2410 1 1100 113524x 1x 2x 335D 24x 1 x 3x 2 x 1x 3 x 235D b :(11)This matrix C is not triangular.It is not so simple to solve for x when we are given b .Actually it is impossible to find the solution to C x D b ,because the three equations either have infinitely many solutions or else no solution :C xD 0Infinitelymany x 24x 1 x 3x 2 x 1x 3 x 235D 2400035is solved by all vectors 24x 1x 2x 335D 24c c c35:(12)26Chapter1.Introduction to Vectors Every constant vector(c;c;c)has zero differences when we go cyclically.This undeter-mined constant c is like the C C that we add to integrals.The cyclic differences have x1 x3in thefirst component,instead of starting from x0D0.The other very likely possibility for C x D b is no solution at all:24x1 x3x2 x1x3 x235D 2 4135351.3.Matrices 27All three vectors u ;v ;w have components adding to zero.Then all their combinations will have b 1C b 2C b 3D 0(as we saw above,by adding the three equations).This is the equation for the plane containing all combinations of u and v .By including w we get no new vectors because w is already on that plane.The original w D .0;0;1/is not on the plane:0C 0C 1¤0.The combinations of u ;v ;w fill the whole three-dimensional space.We know this already,because the solution x D S b in equation (6)gave the right combination to produce any b .The two matrices A and C ,with third columns w and w ,allowed me to mention two key words of linear algebra:independence and dependence.The first half of the course will develop these ideas much further—I am happy if you see them early in the two examples:u ;v ;w are independent .No combination except 0u C 0v C 0w D 0gives b D 0.u ;v ;w are dependent .Other combinations (specifically u C v C w )give b D 0.You can picture this in three dimensions.The three vectors lie in a plane or they don’t.Chapter 2has n vectors in n -dimensional space.Independence or dependence is the key point.The vectors go into the columns of an n by n matrix:Independent columns:A x D 0has one solution.A is an invertible matrix .Dependent columns:A x D 0has many solutions.A is a singular matrix .Eventually we will have n vectors in m -dimensional space.The matrix A with those n columns is now rectangular (m by n ).Understanding A x D b is the problem of Chapter 3.1.Matrix times vector :A x D combination of the columns of A .2.The solution to A x D b is x D A 1b ,when A is an invertible matrix.3.The difference matrix A is inverted by the sum matrix S D A 1.4.The cyclic matrix C has no inverse.Its three columns lie in the same plane.Those dependent columns add to the zero vector.C x D 0has many solutions.5.This section is looking ahead to key ideas,not fully explained yet.1.3A Change the southwest entry a 31of A (row 3,column 1)to a 31D 1:A x D b 24100 1101 113524x 1x 2x 335D 24x 1 x 1C x 2x 1 x 2C x 335D 24b 1b 2b 335:Find the solution x for any b .From x D A 1b read off the inverse matrix A 1.28Chapter 1.Introduction to Vectors Solution Solve the (linear triangular)system A x D b from top to bottom:first x 1D b 1then x 2D b 1C b 2then x 3D b 2C b 3This says that x D A 1b D 241001100113524b 1b 2b 335This is good practice to see the columns of the inverse matrix multiplying b 1;b 2,and b 3.The first column of A 1is the solution for b D .1;0;0/.The second column is the solution for b D .0;1;0/.The third column x of A 1is the solution for A x D b D .0;0;1/.The three columns of A are still independent.They don’t lie in a plane.The combi-nations of those three columns,using the right weights x 1;x 2;x 3,can produce any three-dimensional vector b D .b 1;b 2;b 3/.Those weights come from x D A 1b .1.3B This E is an elimination matrix .E has a subtraction,E 1has an addition.E x D b10 `1 x 1x 2 D b 1b 2 E D 10 `1The first equation is x 1D b 1.The second equation is x 2 `x 1D b 2.The inverse will add `x 1D `b 1,because the elimination matrix subtracted `x 1:x D E 1b x 1x 2D b 1`b 1C b 2 D 10`1 b 1b 2E 1D 10`1 1.3C Change C from a cyclic difference to a centered difference producing x 3 x 1:C x D b 24010 1010 103524x 1x 2x 335D 24x 2 0x 3 x 10 x 235D 24b 1b 2b 335:(15)Show that C x D b can only be solved when b 1C b 3D 0.That is a plane of vectors b in three-dimensional space.Each column of C is in the plane,the matrix has no inverse.So this plane contains all combinations of those columns (which are all the vectors C x ).Solution The first component of b D C x is x 2,and the last component of b is x 2.So we always have b 1C b 3D 0,for every choice of x .If you draw the column vectors in C ,the first and third columns fall on the same line.In fact .column 1/D .column 3/.So the three columns will lie in a plane,and C is not an invertible matrix.We cannot solve C x D b unless b 1C b 3D 0.I included the zeros so you could see that this matrix produces “centered differences”.Row i of C x is x i C 1(right of center )minus x i 1(left of center ).Here is the 4by 4centered difference matrix:C x D b 26640100 10100 10100 1037752664x 1x 2x 3x 43775D 2664x 2 0x 3 x 1x 4 x 20 x 33775D 2664b 1b 2b 3b 43775(16)Surprisingly this matrix is now invertible!The first and last rows give x 2and x 3.Then the middle rows give x 1and x 4.It is possible to write down the inverse matrix C 1.But 5by 5will be singular (not invertible )again :::1.3.Matrices29 Problem Set1.31Find the linear combination2s1C3s2C4s3D b.Then write b as a matrix-vector multiplication S pute the dot products(row of S) x:s1D 2411135s2D2401135s3D2400135go into the columns of S.2Solve these equations S y D b with s1;s2;s3in the columns of S:2 4100 110 1113524y1y2y335D2411135and241001101113524y1y2y335D2414935.The sum of thefirst n odd numbers is.The matrix W with those columns is not invertible.5The rows of that matrix W produce three vectors(I write them as columns):r1D 2414735r2D2425835r3D2436935:Linear algebra says that these vectors must also lie in a plane.There must be many combinations with y1r1C y2r2C y3r3D0.Find two sets of y’s.6Which values of c give dependent columns(combination equals zero)?2 4135 124 11c 352410c1100113524c c c2153363530Chapter 1.Introduction to Vectors 7If the columns combine into A x D 0then each row has r x D 0:24a 1a 2a 33524x 1x 2x 335D 2400035By rows 24r 1 x r 2 x r 3 x 35D 2400035:The three rows also lie in a plane.Why is that plane perpendicular to x ?8Moving to a 4by 4difference equation A x D b ,find the four components x 1;x 2;x 3;x 4.Then write this solution as x D S b to find the inverse matrix S D A 1:A x D 26641000 11000 11000 1137752664x 1x 2x 3x 43775D 2664b 1b 2b 3b 43775D b :9What is the cyclic 4by 4difference matrix C ?It will have 1and 1in each row.Find all solutions x D .x 1;x 2;x 3;x 4/to C x D 0.The four columns of C lie in a “three-dimensional hyperplane”inside four-dimensional space.10A forward difference matrix is upper triangular:z D 24 1100 1100 13524z 1z 2z 335D 24z 2 z 1z 3 z 20 z 335D 24b 1b 2b 335D b :Find z 1;z 2;z 3from b 1;b 2;b 3.What is the inverse matrix in z D 1b ?11Show that the forward differences .t C 1/2 t 2are 2t C 1D odd numbers .As in calculus,the difference .t C 1/n t n will begin with the derivative of t n ,which is。

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introduction to linear algebra 5th edition 中译
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题目: 《[线性代数引论第五版中译]》:理解线性代数的步骤和关键概念
引言:
线性代数作为数学的一个重要分支,研究了向量空间和线性映射的性质与结构,是解决各种数学和工程问题的基础。

而在学习线性代数的过程中,作为一本经典教材,《线性代数引论第五版中译》提供了详尽和深入的内容,对于初学者来说,理解其中的步骤和关键概念是非常重要的。

本文将一步一步回答关于该教材的一些常见问题,帮助读者更好地掌握线性代数。

第一步:了解线性代数的基本定义和概念(Introduction)
在学习《线性代数引论第五版中译》之前,首先需要了解线性代数的基本定义和概念。

线性代数主要研究向量、矩阵和线性变换等概念。

向量是线性代数中的基本元素,它可以表示方向和大小。

矩阵是由数构成的矩形阵列,用于表示线性映射和线性方程组等。

线性变换是指一个向量空间到另一个向量空间的映射,保持向量间的线性关系。

第二步:掌握向量空间的概念和性质(Chapter 1)
向量空间是线性代数中最重要的概念之一,它是由一组满足一定条件的向量所构成的集合。

在学习第一章时,需要掌握向量空间的定义、线性组合、
线性相关性和线性无关性等重要概念。

了解这些基本概念,可以帮助我们理解向量空间的性质和操作。

第三步:理解线性变换和矩阵的关系(Chapter 2)
线性变换和矩阵是线性代数中核心的概念。

一个线性变换可以由一个矩阵来表示,而一个矩阵也可以表示一个线性变换。

在第二章,我们需要理解线性变换和矩阵之间的关系,掌握线性变换的定义、线性变换的运算和性质,以及矩阵的乘法和逆矩阵等重要概念。

第四步:解析线性方程组和矩阵的特征值和特征向量(Chapter 3)
线性方程组是线性代数中的一个重要应用。

在第三章,我们需要学习如何解析线性方程组,理解矩阵的秩、行列式和逆矩阵的相关概念。

此外,还需要掌握矩阵的特征值和特征向量的概念,这对于分析和处理线性变换的性质和行为非常重要。

第五步:应用学习理论解决实际问题(Chapter 4-6)
在第四章至第六章,我们将了解线性变换的标准形式、正交性、正定性等概念,以及如何将线性代数应用于实际问题的求解。

这些章节提供了线性代数在工程和科学领域中的应用,从而帮助我们更好地理解线性代数在实际问题中的解决方法。

结论:
理解《线性代数引论第五版中译》的步骤和关键概念是学习线性代数的关键。

通过掌握线性代数的基本概念和定义,理解向量空间、线性变换和矩阵的关系,以及应用线性代数解决实际问题的方法,我们将能够更好地应用线性代数解决各种数学和工程问题。

希望本文能够帮助读者在学习线性代数时事半功倍,取得更好的学习效果。

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