Signals and Systems(4)
Chapter1 Signals and Systems

Example Fig 3
1.2 Transformations of The independent Variable
1.2.3 Even and Odd Signals
1.2 Transformations of The indepenຫໍສະໝຸດ ent Variable2
The total energy over an infinite time interval in discrete-time is defined as:
E lim
N n N
| x[n] |
2
N
n
| x[n] |2
1.1 Continuous-time and Discretetime Signals
Preface
◆Chapter1
Signals and Systems
◆ Chapter2
◆ Chapter3
Linear Time-invariant Systems
Fourier Series representation of periodic
signals
◆ Chapter4 ◆ Chapter5
Sinusoidal Signals(正弦信号):
1.3 Exponential And Sinusoidal Signals
1.3.1 Continuous-time Complex Exponential and Sinusoidal Signals
Sinusoidal Signals(正弦信号):
1 [ n] 0 n0 n0
1
[n]
2
signal and system 英文原版书

signal and system 英文原版书Title: An Overview of the Book "Signal and System"Introduction:The book "Signal and System" is an essential resource for anyone interested in understanding the fundamentals of signal processing and system analysis. It provides a comprehensive and in-depth exploration of the concepts, theories, and applications related to signals and systems. This article aims to provide a detailed overview of the book, highlighting its key points and relevance.I. Fundamental Concepts of Signals and Systems:1.1 Definition and Properties of Signals:- Explanation of signals as time-varying or spatially varying quantities.- Discussion on continuous-time and discrete-time signals.- Description of signal properties such as amplitude, frequency, and phase.1.2 Classification of Signals:- Overview of different types of signals including periodic, aperiodic, deterministic, and random signals.- Explanation of energy and power signals.- Introduction to common signal operations such as time shifting, scaling, and time reversal.1.3 System Classification and Properties:- Definition and classification of systems as linear or nonlinear, time-invariant or time-varying.- Explanation of system properties like causality, stability, and linearity.- Introduction to system representations such as differential equations, transfer functions, and state-space models.II. Time-Domain Analysis of Signals and Systems:2.1 Convolution and Correlation:- Detailed explanation of convolution and its significance in system analysis.- Discussion on correlation as a measure of similarity between signals.- Application of convolution and correlation in practical scenarios.2.2 Fourier Series and Transform:- Introduction to Fourier series and its representation of periodic signals.- Explanation of Fourier transform and its application in analyzing non-periodic signals.- Discussion on the properties of Fourier series and transform.2.3 Laplace Transform:- Overview of Laplace transform and its use in solving differential equations.- Explanation of the relationship between Laplace transform and frequency response of systems.- Application of Laplace transform in system analysis and design.III. Frequency-Domain Analysis of Signals and Systems:3.1 Frequency Response:- Definition and interpretation of frequency response.- Explanation of magnitude and phase response.- Analysis of frequency response using Bode plots.3.2 Filtering and Filtering Techniques:- Introduction to digital and analog filters.- Discussion on different filter types such as low-pass, high-pass, band-pass, and band-stop filters.- Explanation of filter design techniques including Butterworth, Chebyshev, and Elliptic filters.3.3 Sampling and Reconstruction:- Explanation of sampling theorem and its importance in signal processing.- Overview of sampling techniques and their impact on signal reconstruction.- Discussion on anti-aliasing filters and reconstruction methods.IV. System Analysis and Stability:4.1 System Response and Impulse Response:- Explanation of system response to different input signals.- Introduction to impulse response and its relationship with system behavior.- Analysis of system stability based on impulse response.4.2 Transfer Function and Frequency Domain Analysis:- Definition and interpretation of transfer function.- Explanation of frequency domain analysis using transfer function.- Application of transfer function in system design and analysis.4.3 Feedback Systems and Control:- Overview of feedback systems and their role in control theory.- Explanation of stability analysis and design using control theory.- Discussion on PID controllers and their applications.V. Applications of Signal and System Theory:5.1 Communication Systems:- Explanation of modulation techniques and their role in communication systems.- Overview of demodulation techniques and their significance.- Discussion on error control coding and channel equalization.5.2 Digital Signal Processing:- Introduction to digital signal processing and its applications.- Explanation of digital filters and their role in signal processing.- Overview of image and speech processing techniques.5.3 Signal Processing in Biomedical Engineering:- Application of signal processing in biomedical signal analysis.- Discussion on medical imaging techniques such as MRI and CT scans.- Explanation of signal processing methods used in ECG and EEG analysis.Conclusion:The book "Signal and System" provides a comprehensive and detailed exploration of the fundamental concepts, theories, and applications related to signals and systems. It covers a wide range of topics including signal classification, system analysis, frequency-domain analysis, stability, and various applications. By studying this book, readers can gain a solid understanding of signal and system theory, which is essential in various fields such as communication, digital signal processing, and biomedical engineering.。
信号与系统目录(Signal and system directory)

信号与系统目录(Signal and system directory)Chapter 1 signals and systems1.1 INTRODUCTION1.2 signalContinuous signals and discrete signalsTwo. Periodic signals and aperiodic signalsThree, real signal and complex signalFour. Energy signal and power signalThe basic operation of 1.3 signalAddition and multiplicationTwo, inversion and TranslationThree, scale transformation (abscissa expansion)1.4 step function and impulse functionFirst, step function and impulse functionTwo. Definition of generalized function of impulse functionThree. The derivative and integral of the impulse functionFour. Properties of the impulse functionDescription of 1.5 systemFirst, the mathematical model of the systemTwo. The block diagram of the systemCharacteristics and analysis methods of 1.6 systemLinearTwo, time invarianceThree, causalityFour, stabilityOverview of five and LTI system analysis methodsExercise 1.32The second chapter is the time domain analysis of continuous systemsThe response of 2.1LTI continuous systemFirst, the classical solution of differential equationTwo, about 0- and 0+ valuesThree, zero input responseFour, zero state responseFive, full response2.2 impulse response and step responseImpulse responseTwo, step response2.3 convolution integralConvolution integralTwo. The convolution diagramThe properties of 2.4 convolution integralAlgebraic operations of convolutionTwo. Convolution of function and impulse function Three. Differential and integral of convolutionFour. Correlation functionExercise 2.34The third chapter is the time domain analysis of discretesystemsThe response of 3.1LTI discrete systemsDifference and difference equationsTwo. Classical solutions of difference equationsThree, zero input responseFour, zero state response3.2 unit sequence and unit sequence responseUnit sequence and unit step sequenceTwo, unit sequence response and step response3.3 convolution sumConvolution sumTwo. The diagram of convolution sumThree. The nature of convolution sum3.4 deconvolutionExercise 3.27The fourth chapter is Fourier transform and frequency domainanalysis of the systemThe 4.1 signal is decomposed into orthogonal functions Orthogonal function setTwo. The signal is decomposed into orthogonal functions 4.2 Fourier seriesDecomposition of periodic signalsTwo, Fourier series of odd even functionThree. Exponential form of Fu Liye seriesThe spectrum of 4.3 period signalFrequency spectrum of periodic signalTwo, the spectrum of periodic matrix pulseThree. The power of periodic signal4.4 the spectrum of aperiodic signalsFirst, Fu Liye transformTwo. Fourier transform of singular functionsProperties of 4.5 Fourier transformLinearTwo, parityThree, symmetryFour, scale transformationFive, time shift characteristicsSix, frequency shift characteristicsSeven. Convolution theoremEight, time domain differential and integral Nine, frequency domain differential and integral Ten. Correlation theorem4.6 energy spectrum and power spectrumEnergy spectrumTwo. Power spectrumFourier transform of 4.7 periodic signals Fourier transform of sine and cosine functionsTwo. Fourier transform of general periodic functionsThree 、 Fu Liye coefficient and Fu Liye transformFrequency domain analysis of 4.8 LTI systemFrequency responseTwo. Distortionless transmissionThree. The response of ideal low-pass filter4.9 sampling theoremSampling of signalsTwo. Time domain sampling theoremThree. Sampling theorem in frequency domainFourier analysis of 4.10 sequencesDiscrete Fourier series DFS of periodic sequencesTwo. Discrete time Fourier transform of non periodic sequences DTFT4.11 discrete Fu Liye and its propertiesDiscrete Fourier transform (DFT)Two. The properties of discrete Fourier transformExercise 4.60The fifth chapter is the S domain analysis of continuous systems 5.1 Laplasse transformFirst, from Fu Liye transform to Laplasse transformTwo. Convergence domainThree, (Dan Bian) Laplasse transformThe properties of 5.2 Laplasse transformLinearTwo, scale transformationThree, time shift characteristicsFour, complex translation characteristicsFive, time domain differential characteristicsSix, time domain integral characteristicsSeven. Convolution theoremEight, s domain differential and integralNine, initial value theorem and terminal value theorem5.3 Laplasse inverse transformationFirst, look-up table methodTwo, partial fraction expansion method5.4 complex frequency domain analysisFirst, the transformation solution of differential equation Two. System functionThree. The s block diagram of the systemFour 、 s domain model of circuitFive, Laplasse transform and Fu Liye transform5.5 bilateral Laplasse transformExercise 5.50The sixth chapter is the Z domain analysis of discrete systems 6.1 Z transformFirst, transform from Laplasse transform to Z transformTwo, z transformThree. Convergence domainProperties of 6.2 Z transformLinearTwo. Displacement characteristicsThree, Z domain scale transformFour. Convolution theoremFive, Z domain differentiationSix, Z domain integralSeven, K domain inversionEight, part sumNine, initial value theorem and terminal value theorem 6.3 inverse Z transformFirst, power series expansion methodTwo, partial fraction expansion method6.4 Z domain analysisThe Z domain solution of difference equationTwo. System functionThree. The Z block diagram of the systemFour 、 the relation between s domain and Z domainFive. Seeking the frequency response of discrete system by means of DTFTExercise 6.50The seventh chapter system function7.1 system functions and system characteristicsFirst, zeros and poles of the system functionTwo. System function and time domain responseThree. System function and frequency domain responseCausality and stability of 7.2 systemsFirst, the causality of the systemTwo, the stability of the system7.3 information flow graphSignal flow graphTwo, Mason formulaStructure of 7.4 systemFirst, direct implementationTwo. Implementation of cascade and parallel connectionExercise 7.39The eighth chapter is the analysis of the state variables of the system8.1 state variables and state equationsConcepts of state and state variablesTwo. State equation and output equationEstablishment of state equation for 8.2 continuous systemFirst, the equation is directly established by the circuit diagramTwo. The equation of state is established by the input-output equationEstablishment and Simulation of state equations for 8.3discrete systemsFirst, the equation of state is established by the input-output equationTwo. The system simulation is made by the state equationSolution of state equation of 8.4 continuous systemFirst, the Laplasse transform method is used to solve the equation of stateTwo, the system function matrix H (z) and the stability of the systemThree. Solving state equation by time domain methodSolution of state equation for 8.5 discrete systemsFirst, the time domain method is used to solve the state equations of discrete systemsTwo. Solving the state equation of discrete system by Z transformThree, the system function matrix H (z) and the stability of the systemControllability and observability of 8.6 systemsFirst, the linear transformation of state vectorTwo, the controllability and observability of the systemExercise 8.32Appendix a convolution integral tableAppendix two convolution and tableAppendix three Fourier coefficients table of commonly used periodic signalsAppendix four Fourier transform tables of commonly used signalsAppendix five Laplasse inverse exchange tableAppendix six sequence of the Z transform table。
信号与系统SignalsandSystemsppt课件

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一、基本信号的MATLAB表示
% rectpuls
t=0:0.001:4; T=1; ft=rectpuls(t-2*T,T); plot(t,ft) axis([0,4,-0.5,1.5])
rand
产生(0,1)均匀分布随机数矩阵
randn 产生正态分布随机数矩阵
四、数组
2. 数组的运算
数组和一个标量相加或相乘 例 y=x-1 z=3*x
2个数组的对应元素相乘除 .* ./ 例 z=x.*y
确定数组大小的函数 size(A) 返回值数组A的行数和列数(二维) length(B) 确定数组B的元素个数(一维)
0.3
0.2
0.1
function [f,k]=impseq(k0,k1,k2) 0
-50 -40 -30 -20 -10
0
10 20 30 40 50
%产生 f[k]=delta(k-k0);k1<=k<=k2
k=[k1:k2];f=[(k-k0)==0];
k0=0;k1=-50;k2=50;
[f,k]=impseq(k0,k1,k2);
已知三角波f(t),用MATLAB画出的f(2t)和f(2-2t) 波形
信号与系统张晔版第四章ppt

L[u(t)] est dt est 1
0
s
s
0
u(t) 1 s
(2) 单边指数信号 f (t) eatu(t)
延时信号
→ 对比傅里叶变换? 双边
L[eat ] eat est dt e(as)t 1
0
as
as
0
eat u(t) 1 sa
( a)
哈尔滨工业大学图象与信息技术研究所
L f (t t0 )u(t t0 ) F (s)est0
→
L
f
(at
t0 )u(at
t0 )
1 a
F
s a
e
s a
t0
(2) 先尺度、后平移
L
f
(at)u(at)
1 a
F
s a
→
L
f
(at
t0 )u(at
t0 )
1 a
F
s a
e
s a
t0
哈尔滨工业大学图象与信息技术研究所
4.2.6 时域微分特性
推而广之:
L
d n f (t)
dt n
sn F (s)
n 1 r 0
snr 1
f
(r) (0)
式中
f
(r)
(0)是r阶导数
d
r f (t) dt r
在0-时刻的取值。特别是,如果它们都为0,则
L
df (t dt
)
sF
(s)
L
d
2f dt
(t
2
)
s2F(s)
i 1
i 1
在应用中,可实现复杂信号的分解。
4.2.2 时域平移特性
signals and systems_introduction

I(x,y)
What is a Signal (信号)?
Definitions A Signal is formally defined as a function of one or more variables that conveys information on the nature of a physical phenomenon. 信号是一个或多个变量的函数,携带着某个物 理现象的信息。
3. Four different forms of Fourier Transform:
Continuous and Periodic Discrete and Periodic Continuous and Aperiodic Discrete and Aperiodic
4. Use the right one !!!
第三章 信号与线性非时变系统的傅里叶分析 (Fourier Representations for signals and Linear TimeInvariant Systems ) 离散时间周期与非周期信号、连续时间周期与非周期信号的傅里叶分析; 傅里叶分析的性质;LTI系统的频域分析。
Contents
Signals and Systems
--- One of the most important courses for us!
陈布雨 技术中心B区217室 图书馆720
Contents
第一章 信号与系统简介 (Introduction) 介绍信号与系统的基本概念; 信号分类及基本信号;系统分类和特性。 第二章 线性非时变系统的时域分析 (Time-Domain Representations for Linear TimeInvariant Systems) 单位冲激响应和单位脉冲响应,卷积积分和卷积和;系统的互联;系统 的响应求解;系统的方框图表示, 系统的状态空间分析。
信号与系统(Signals and Systems)

信号与系统(Signals and Systems)信号与系统(Signals and Systems)是电子信息工程领域中非常重要的一门课程。
它是研究信号在各种系统中传输、变换和处理的学科,通常需要一些微积分和线性代数的基础知识。
信号和系统理论不仅应用于工程中,也广泛出现在生物医学、电力系统、通信系统中。
总的来说,信号与系统可以分为三个部分:信号、系统和信号处理。
下面我将分别介绍这三个方面的内容。
一、信号信号是代表某种信息的物理量,可以是电信号、光信号、声波等。
常见的信号包括连续信号和离散信号。
连续信号指的是在一段时间内连续地变化的信号,可以用函数f(t) 来表示。
离散信号则是在特定的时间点(离散时间)上产生的信号,表示为序列{xn}。
无论是连续信号还是离散信号,它们都遵循一些基本的信号特性,比如幅度、频率、相位、周期和能量等。
二、系统系统是用于处理信号的工具,可以是电路、滤波器、放大器或者是数字信号处理器。
在信号和系统领域,系统可以被分为连续系统和离散系统。
连续系统指的是输入和输出都是连续信号的系统,比如电路。
离散系统则是输入和输出都是离散信号的系统,比如数字滤波器。
系统通常被描述为输入到输出之间的关系,这个关系可以用一个函数 h(t) 或者 h[n] 来表示。
一个系统可以具有不同的特性,比如时域特性、频域特性、稳定性、因果性、线性性和时变性等。
学习系统理论可以帮助我们更好地了解各种信号和系统的行为特点,从而选择合适的系统来处理不同类型的信号。
三、信号处理信号处理指的是对信号进行分析、处理或者变换的过程,可以是模拟信号处理或数字信号处理。
在信号处理领域,我们经常遇到需要从原始信号中提取特定信息的问题,比如噪声消除、滤波、增强等。
常见的信号处理方法包括傅里叶变换、卷积、差分方程、滤波等。
这些方法可以在时域或者频域中对信号进行变换,得到更有用的信息。
总结信号与系统是一门重要的学科,它主要研究信号在不同系统中传输、变换和处理的过程。
信号与系统第1章-信号与系统的基本概念

1 0
1
t
1 0
2
一半语速信号
4 t
正常语速信号
2倍语速信号
若
a 1 ,波形在t 轴上扩展 1 a 倍。
若 a 1 ,波形在t 轴上压缩1/
a 倍。
信号与系统
SIGNALS & SYSTEMS
第一章 信号与系统的基本概念
前言
§1.1 信号的描述与分类 §1.2 连续时间信号的基本运算与变换 §1.3 系统的描述与分类 §1.4 系统分析方法
♣ 连续时间信号的基本运算主要包括
相加(减)、相乘(除)、微分、积分
♣ 信号波形变换主要指
波形的翻转、平移和展缩 通常是通过对自变量的代换实现
信号与系统
SIGNALS & SYSTEMS
一.信号的相加减
f1(t) 1 0 1
1
f ( t )=f1 ( t )+f2 ( t )
2 1
1
f2 (t)
f1 (t ) f2 (t )
信号与系统
SIGNALS & SYSTEMS
六.信号的时移(波形平移)
连续时间信号的时移定义为
y(t ) f (t t0 )
f (t )
f (t b)
t0为时移量
t t t0
f (t b)
-1
b1
t
(-1+b)
1 (1+b) t
(-1-b)
(1-b)
t
t0>0时右移
t0<0时左移
出现冲激, 其冲激强度 为该处的跳 变量
0
1 2 3
t
0 1
-2
3 (2)
t
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非周期信号傅立叶变换的导出 回顾: 回顾:连续时间周期方波信号的傅立叶级数
从任一时刻t − −t + T积分,为方便起见,积 分区间选 − T / 2 < t < T / 2 1 T1 2T a0 = ∫ dt = 1 ,a0为x(t )的平均值,即周期方波 的占空比 T −T1 T 1 T1 − jkω0t 1 2 e jkω0T1 − e − jkω0T1 − jkω0t T1 |−T1 = ak = ∫ e dt = − e = −T1 T jkω0T kω0T 2j 2 sin( kω0T1 ) = kω0T sin( kπ kπ 2T1 ) T ,k ≠ 0
X ( jω )=∫ x(t )e
−∞
+∞
− jωt
dt
1 +∞ x(t )= ∫ X ( jω )e jωt dω 2π −∞ k = −∞ 此式表明,非周期信号可以分解成无数多个频率连续分布、
1 ak = ∫ x(t )e − jkω0t dt T T+∞ x(t ) = ∑ ak e jkω0t
T=4T1,占空比=0.5 占空比= 占空比
π
T=8T1,占空比=0.25 占空比= 占空比
π
T=16T1,占空比=0.125 占空比= 占空比
π
sin(kω0T1 ) ,k ≠ 0 假定T=4 T=4, 假定T=4,T1=1,以实际频率为横轴绘图 kπ
2011年7月27日星期三 7 Signals & Systems
2011年7月27日星期三 14 Signals & Systems
号
:连续时间
变换
Representation of Aperiodic Signals: The Continuous-Time Fourier Transform
条件1: 若x(t )平方可积,即∫ x(t ) dt < ∞,则X ( jω )是有限值,
ห้องสมุดไป่ตู้
X ( jω )=F{x(t )} ⇔ X ( jω ) ← F x(t ) → −1 x(t )=F { X ( jω )}
2011年7月27日星期三
12
Signals & Systems
非周期信号的表示: 非周期信号的表示:连续时间傅立叶变换
Representation of Aperiodic Signals: The Continuous-Time Fourier Transform
ˆ ˆ x(t )e − jkω0t dt,由于在 t < T / 2内,x(t ) = x(t ),因此: x(t )e
+∞ −∞ − jkω0t
−T / 2
1 dt = T
∫
+∞
−∞
x(t )e − jkω0t dt 1 X ( jkω0 ) T
10 Signals & Systems
令X ( jω )=∫ x(t )e − jωt dt , 则ak =
−∞ +∞ 2
表明傅立叶变换存在。 条件2: Dirichlet条件: 1、x(t )绝对可积, x(t ) dt < ∞ ∫
−∞ +∞
2、在任何有限区间内,x(t )只有有限个最大值和最小值 3、在任何有限区间内,x(t )有有限个不连续点, 且在每个不连续点都是有限值
仅为充分条件,且两条件不对等
求取图(a)所示信号x(t )的 傅立叶变换,先构造图(b) ˆ 所示的以T为周期的周期信号x(t ) 取积分区间 − T / 2 ≤ t ≤ T / 2,有: ˆ x(t ) = ak = 1 T 1 ak = T
k = −∞
x(t )
ˆ x (t )
∑a e
k
+∞
jkω0t
∫ ∫
T /2
−T / 2 T /2
2011年7月27日星期三 3 Signals & Systems
号 连续时间
: 变换
Representation of Aperiodic Signals: The Continuous-Time Fourier Transform Continuous-
号
:连续时间
变换
Representation of Aperiodic Signals: The Continuous-Time Fourier Transform
T=4T1,占空比=0.5 占空比= 占空比
π
包络线
T=8T1,占空比=0.25 占空比= 占空比
π
T=16T1,占空比=0.125 占空比= 占空比
π
以同一范围的实际频率为横轴绘图,考察周期信号的一个周期, 以同一范围的实际频率为横轴绘图,考察周期信号的一个周期,可 周期越大,采样频率越高, 见,周期越大,采样频率越高,但频谱的包络线形状不变
连续时间
变换
内
连续时间傅立叶变换; 连续时间傅立叶变换 傅立叶级数与傅立叶变换之间的关系; 傅立叶级数与傅立叶变换之间的关系 傅立叶变换的性质; 傅立叶变换的性质 系统的频率响应及系统的频域分析; 系统的频率响应及系统的频域分析;
2011年7月27日星期三
2
Signals & Systems
在时域可以看到,如果一个周期信号的周期趋于无穷大,则 周期信号演变成一个非周期信号;反过来,如果将非周期信 号进行周期性延拓,就一定能形成一个周期信号。 我们把非周期信号看成是周期信号在周期趋于无穷大时的极 限,从而考查连续时间傅立叶级数在 T趋于无穷大时的变化, 就应该能够得到对非周期信号的频域表示方法。 在工程应用中有相当广泛的信号是非周期信号,对非周期信 号应该如何进行分解,什么是非周期信号的频谱表示,线性 时不变系统对非周期信号的响应如何求得,就是这一章要解 决的问题。
k = −∞
∑ X ( jkω0 )e
+∞
jkω0 t
1 ω0 → 2π
T →∞ ,ω0 → 0
∫
+∞
−∞
X ( jω )e jωt dω = x(t )
2011年7月27日星期三
11
Signals & Systems
非周期信号的表示: 非周期信号的表示:连续时间傅立叶变换
Representation of Aperiodic Signals: The Continuous-Time Fourier Transform
X ( jω ) = ∫ e e
0
+∞
− at − jωt
X ( jω ) =
1 a2 + ω 2
x(t )
1
1 1 − ( a + jω ) t ∞ dt = − e |0 = a + jω a + jω -1 ω ∠X ( jω ) = − tg a ∠X ( jω )
X ( jω)
1/ a
1 2a
2011年7月27日星期三 15 Signals & Systems
号
:连续时间
变换
Representation of Aperiodic Signals: The Continuous-Time Fourier Transform
常见信号的傅立叶变换
信号1:x(t ) = e − at u (t ),a > 0
0
t
0
2011年7月27日星期三
−a
a
16
ω
−a
−π / 2
−π / 4
π /4
π /2
a
ω
Signals & Systems
号
:连续时间
变换
Representation of Aperiodic Signals: The Continuous-Time Fourier Transform
信号2:x(t ) = e
2011年7月27日星期三 13 Signals & Systems
号
:连续时间
变换
Representation of Aperiodic Signals: The Continuous-Time Fourier Transform
傅立叶变换的收敛
设X(jω)…÷ x(t)ŠXƒœ•Μ7 么 变换, 么条件 趋 号x(t)? 1 +∞ ˆ x ( t )= X ( j ω )e jω t d ω 2π ∫− ∞
X ( jω ) = ∫ e
−∞ +∞ −a t
−a t
,a > 0
dt = ∫ e e
−∞ 0 at − jωt
e
− jω t
dt + ∫ e − at e − jωt dt =
0
+∞
=
1 1 2a + = 2 a + jω a − jω a + ω 2
信号为实偶函数,傅立叶变换也为实偶函数,这点和傅立叶级数相同。 信号为实偶函数,傅立叶变换也为实偶函数,这点和傅立叶级数相同。 因此,幅频响应为实偶函数, 因此,幅频响应为实偶函数,相频响应为零
8ω0
2T 假定T 不变,随着周期T的增长 占空比减小, 的增长, 假定 1不变,随着周期 的增长,占空比减小,基频 sin(kπ 1 ) T ,k ≠ 0 ω0随着减小,因此以上三个交点实际频率相等。 随着减小,因此以上三个交点实际频率相等。 kπ
2011年7月27日星期三 6 Signals & Systems
ω
ω=kω0
不变时, 的包络线不变, 就是Ta 的采样线,随着T的 当T1不变时,Tak的包络线不变,而ak就是 k的采样线,随着 的 增加, 减小,采样密度越来越高。 变得无穷大时, 增加,ω0减小,采样密度越来越高。当T变得无穷大时,周期方波 变得无穷大时 趋近于一个矩形脉冲,傅立叶级数系数就趋近于这条包络线, 趋近于一个矩形脉冲,傅立叶级数系数就趋近于这条包络线,即矩 形脉冲的傅立叶变换。 形脉冲的傅立叶变换。