数字滤波器外文翻译
数字滤波器
数字滤波器是对数字信号进行滤波处理以得到期望的响应特性的离散时间系统。作为一种电子滤波器，数位滤波器与完全工作在模拟信号域的模拟滤波器不同。数字滤波器工作在数字信号域，它处理的对象是经由采样器件将模拟信号转换而得到的数字信号。
数字滤波器的工作方式与模拟滤波器也完全不同：后者完全依靠电阻、电容、晶体管等电子元件组成的物理网络实现滤波功能；而前者是通过数字运算器件对输入的数字信号进行运算和处理，从而实现设计要求的特性。
数字滤波器理论上可以实现任何可以用数学算法表示的滤波效果。数字滤波器的两个主要限制条件是它们的速度和成本。数字滤波器不可能比滤波器内部的计算机的运算速度更快。但是随着集成电路成本的不断降低，数字滤波器变得越来越常见并且已经成为了如收音机、蜂窝电话、立体声接收机这样的日常用品的重要组成部分。
数字滤波器一般由寄存器、延时器、加法器和乘法器等基本数字电路实现。随着集成电路技术的发展，其性能不断提高而成本却不断降低，数字滤波器的应用领域也因此越来越广。按照数字滤波器的特性，它可以被分为线性与非线性、因果与非因果、无限脉冲响应（IIR）与有限脉冲响应（FIR）等等。其中，线性时不变的数字滤波器是最基本的类型；而由于数字系统可以对延时器加以利用，因此可以引入一定程度的非因果性，获得比传统的因果滤波器更灵活强大的特性；相对于IIR滤波器，FIR滤波器有着易于实现和系统绝对稳定的优势，因此得到广泛的应用；对于时变系统滤波器的研究则导致了以卡尔曼滤波为代表的自适应滤波理论
数字滤波器具有比模拟滤波器更高的精度，甚至能够实现后者在理论上也无法达到的性能。例如，对于数字滤波器来说很容易就能够做到一个1000Hz 的低通滤波器允许999Hz 信号通过并且完全阻止1001Hz 的信号，模拟滤波器无法区分如此接近的信号。
数字滤波器相比模拟滤波器有更高的信噪比。这主要是因为数字滤波器是以数字器件执行运算，从而避免了模拟电路中噪声（如电阻热噪声）的影响。数字滤波器中主要的噪声源是在数字系统之前的模拟电路引入的电路噪声以及在数字系统输入端的模数转换过程中产生的量化噪声。这些噪声在数字系统的运算中可能会被放大，因此在设计数字滤波器时需要采用合适的结构，以降低输入噪声对系统性能的影响。
数字滤波器还具有模拟滤波器不能比拟的可靠性。组成模拟滤波器的电子元件的电路特性会随着时间、温度、电压的变化而漂移，而数字电路就没有这种问题。只要在数字电路的工作环境下，数字滤波器就能够稳定可靠的工作。
由于奈奎斯特采样定理，数字滤波器的处理能力受到系统采样频率的限制。如果输入信号的频率分量包含超过滤波器1/2采样频率的分量时，数字滤波器因为数字系统的“混叠”而不能正常工作。如果超出1/2采样频率的频率分量不占主要地位，通常的解决办法是在模数转换电路之前放置一个低通滤波器（即抗混叠滤波器）将超过的高频成分滤除。否则就必须用模拟滤波器实现要求的功能。
线性移不变的数字滤波器包括无限长脉冲响应滤波器（IIR滤波器）和有限长脉冲响应滤波器（FIR滤波器）两种。这两种滤波器的系统函数可以统一以Z 变换表示为：
当时，M就是IIR滤波器的阶数，表示系统中反馈环的个数。由于反馈的存在，IIR滤波器的脉冲响应为无限长，因此得名。若A(z) = 1，则系统的脉冲响应的长度为N+1，故而被称作FIR滤波器。
IIR滤波器的优点在于，其设计可以直接利用模拟滤波器设计的成果，因为模拟滤波器本身就是无限长冲激响应的。通常IIR滤波器设计的过程如下：首先根据滤波器参数要求设计对应的模拟滤波器（如巴特沃斯滤波器、切比雪夫滤波器等等），然后通过映射（如脉冲响应不变法、双线性映射等等）将模拟滤波器变换为数字滤波器，从而决定IIR滤波器的参数。IIR滤波器的重大缺点在于，由于存在反馈其稳定性不能得到保证。另外，反馈还使IIR滤波器的数字运算可能溢出。
FIR滤波器最重要的优点就是由于不存在系统极点，FIR滤波器是绝对稳定的系统。FIR滤波器还确保了线性相位，这在信号处理中也非常重要。此外，由于不需要反馈，FIR滤波器的实现也比IIR滤波器简单。FIR滤波器的缺点在于它的性能不如同样阶数的IIR滤波器，不过由于数字计算硬件的飞速发展，这一点已经不成为问题。再加上引入计算机辅助设计，FIR滤波器的设计也得到极大的简化。
Digital Filter
Digital filter is filtered to digital signal processing to achieve the desired response characteristics of discrete-time system. As a kind of electronic filters, digital filter and all work in analog signals domain simulation filter is different. Digital filter work in digital signal domain, it handles objects through sampling device is analog signal conversion for digital signals.
Digital filter way of working and simulation filter also completely different: the latter depend entirely on the resistor, capacitor, transistor, and other electronic components of physical network realization filter function; While the former is through digital computing devices for the entry of digital signal calculations and processing, thus realize the requirement of design characteristics.
Digital filter theory can achieve any can use mathematical algorithm the filtering effect said. Digital filter's two main constraints is their speed and cost. Digital filter impossible internal computer than filter the faster. But as the integrated circuit costs continue to reduce, digital filter is becoming more and more common and has become such as radio, cell phones, stereo receivers such an important part of daily articles.
Digital filter generally by registers, delay device, on time-multiplier adder and basic digital circuit implementation. Along with the development of the integrated circuit technology, its with improving performance and cost is lower, digital filter application fields and therefore more and more widely. According to the characteristics of digital filter, it can be divided into linear and nonlinear, causal and the causal, infinite impulse response (IIR) and finite impulse response (FIR), etc. Among them, when the constant linear digital filter is the most basic type; And as a result of digital system can use them to delay device, so can introduce some degree of the causality, get more than traditional causal filter the characteristics of flexible strong; Relative to IIR filter, FIR filters have easy to realize and system is stable advantage, so widely applied; For time-varying system filter research is caused by kalman filter, as a representative of the adaptive filter theory
Digital filters with higher precision than analog filter, even can realize the latter in theory cannot achieve performance. For example, it is very easy for digital filter is
able to do a 1000Hz allowed the low-pass filter and completely prevent 999Hz signal through 1001Hz signal, the simulation filter can't distinguish so close to signal.
Digital filters with a higher than analog filter SNR. This is mainly because digital filter based on digital devices perform operation so as to avoid the analog circuits noise (such as resistors thermal noise) influence. Digital filters the main noise source is in digital system introduced before the analog circuit noise and in digital system input to produce analog-to-digital conversion of quantization noise. These noise in digital system in the operations of may be amplified, so in design digital filter can be used to reduce the appropriate structure of input noise effect the performance of the system.
Digital filter also has not reliability simulation filter. Of analog filter circuits characteristic of electronic components with time, temperature, voltage change and drift, and digital circuit is no such problem. As long as the work environment in a digital circuit, digital filters can stable and reliable work.
Because Nyquist sampling theorem Nyquist sampling theorem (en: the processing, digital filters) sampling frequency by system of ability to limit. If the input signal frequency component contains more than filter 1/2 sampling frequency component, digital filters for digital systems "aliasing" and can't work normally. If exceed 1/2 sampling frequency frequency weight not predominant, usually solution is placed in frequency-field circuit before one low-pass filter (namely fight aliasing filter) will exceed filter the high frequency components. Otherwise we must realize with the simulated filter required functions.
At the time, M is the order number IIR filter, said the number of feedback loops in the system. Due to the existence of IIR filter, feedback the impulse response to an infinite long, therefore the name. If A (z) = 1, it is the length of the impulse response system for N + 1, so called FIR filter.
Linear moving constant digital filter, including an infinite long impulse response filter (IIR filter) and limited long impulse response filter (FIR filter) two kinds. These two kinds of filter system function can be unified with Z transformation expressed as: The advantages of IIR filter is that its design can directly using simulation filter design results, because analog filter itself is an infinite long impulse response. Usually IIR filter design process are as follows: first of all, according to the requirements of the design parameters of the corresponding filters simulated filter (such as bart hepworth filter, chebyshev filters, etc), and then by mapping (such as pulse response
don't strain and bilinear map, etc.) will transform into digital filter simulated filter, to decide IIR filter parameters. The major disadvantage is IIR filter, because it has feedback its stability cannot be guaranteed. In addition, feedback still make IIR filter number operations may overflow.
FIR filter is the most important advantages, because they do not exist system poles, FIR filters is absolutely stable system. FIR filter also ensures that the linear phase in signal processing, this also is very important. In addition, because do not need feedback, the realization of FIR filters than IIR filter simple. FIR filter's weakness is its performance as the same order number IIR filter, but due to the rapid development of digital computing hardware, this is not a problem. Plus introducing computer aided design, the design of FIR filters have also been great simplified.
传感器技术论文中英文对照资料外文翻译文献
中英文对照资料外文翻译文献 附件1：外文资料翻译译文 传感器新技术的发展 传感器是一种能将物理量、化学量、生物量等转换成电信号的器件。输出信号有不同形式，如电压、电流、频率、脉冲等，能满足信息传输、处理、记录、显示、控制要求，是自动检测系统和自动控制系统中不可缺少的元件。如果把计算机比作大脑，那么传感器则相当于五官，传感器能正确感受被测量并转换成相应输出量，对系统的质量起决定性作用。自动化程度越高，系统对传感器要求越高。在今天的信息时代里，信息产业包括信息采集、传输、处理三部分，即传感技术、通信技术、计算机技术。现代的计算机技术和通信技术由于超大规模集成电路的飞速发展，而已经充分发达后，不仅对传感器的精度、可靠性、响应速度、获取的信息量要求越来越高，还要求其成本低廉且使用方便。显然传统传感器因功能、特性、体积、成本等已难以满足而逐渐被淘汰。世界许多发达国家都在加快对传感器新技术的研究与开发，并且都已取得极大的突破。如今传感器新技术的发展，主要有以下几个方面： 利用物理现象、化学反应、生物效应作为传感器原理，所以研究发现新现象与新效应是传感器技术发展的重要工作，是研究开发新型传感器的基础。日本夏普公司利用超导技术研制成功高温超导磁性传感器，是传感器技术的重大突破，其灵敏度高，仅次于超导量子干涉器件。它的制造工艺远比超导量子干涉器件简单。可用于磁成像技术，有广泛推广价值。 利用抗体和抗原在电极表面上相遇复合时，会引起电极电位的变化，利用这一现象可制出免疫传感器。用这种抗体制成的免疫传感器可对某生物体内是否有这种抗原作检查。如用肝炎病毒抗体可检查某人是否患有肝炎，起到快速、准确作用。美国加州大学巳研制出这类传感器。 传感器材料是传感器技术的重要基础，由于材料科学进步，人们可制造出各种新型传感器。例如用高分子聚合物薄膜制成温度传感器；光导纤维能制成压力、流量、温度、位移等多种传感器；用陶瓷制成压力传感器。
图像处理中值滤波器中英文对照外文翻译文献
中英文资料对照外文翻译 一、英文原文 A NEW CONTENT BASED MEDIAN FILTER ABSTRACT In this paper the hardware implementation of a contentbased median filter suitabl e for real-time impulse noise suppression is presented. The function of the proposed ci rcuitry is adaptive; it detects the existence of impulse noise in an image neighborhood and applies the median filter operator only when necessary. In this way, the blurring o f the imagein process is avoided and the integrity of edge and detail information is pre served. The proposed digital hardware structure is capable of processing gray-scale im ages of 8-bit resolution and is fully pipelined, whereas parallel processing is used to m inimize computational time. The architecturepresented was implemented in FPGA an d it can be used in industrial imaging applications, where fast processing is of the utm ost importance. The typical system clock frequency is 55 MHz. 1. INTRODUCTION Two applications of great importance in the area of image processing are noise filtering and image enhancement [1].These tasks are an essential part of any image pro cessor,whether the final image is utilized for visual interpretation or for automatic an alysis. The aim of noise filtering is to eliminate noise and its effects on the original im age, while corrupting the image as little as possible. To this end, nonlinear techniques (like the median and, in general, order statistics filters) have been found to provide mo re satisfactory results in comparison to linear methods. Impulse noise exists in many p ractical applications and can be generated by various sources, including a number of man made phenomena, such as unprotected switches, industrial machines and car ign ition systems. Images are often corrupted by impulse noise due to a noisy sensor or ch annel transmission errors. The most common method used for impulse noise suppressi on n forgray-scale and color images is the median filter (MF) [2].The basic drawback o f the application of the MF is the blurringof the image in process. In the general case,t he filter is applied uniformly across an image, modifying pixels that arenot contamina ted by noise. In this way, the effective elimination of impulse noise is often at the exp ense of an overalldegradation of the image and blurred or distorted features[3].In this paper an intelligent hardware structure of a content based median filter (CBMF) suita ble for impulse noise suppression is presented. The function of the proposed circuit is to detect the existence of noise in the image window and apply the corresponding MF
电子信息工程专业课程翻译中英文对照表
电子信息工程专业课程名称中英文翻译对照 （2009级培养计划）
实践环节翻译
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无线传感器网络论文中英文资料对照外文翻译
中英文资料对照外文翻译 基于网络共享的无线传感网络设计 摘要：无线传感器网络是近年来的一种新兴发展技术，它在环境监测、农业和公众健康等方面有着广泛的应用。在发展中国家，无线传感器网络技术是一种常用的技术模型。由于无线传感网络的在线监测和高效率的网络传送，使其具有很大的发展前景，然而无线传感网络的发展仍然面临着很大的挑战。其主要挑战包括传感器的可携性、快速性。我们首先讨论了传感器网络的可行性然后描述在解决各种技术性挑战时传感器应产生的便携性。我们还讨论了关于孟加拉国和加利 尼亚州基于无线传感网络的水质的开发和监测。 关键词：无线传感网络、在线监测 1.简介 无线传感器网络，是计算机设备和传感器之间的桥梁，在公共卫生、环境和农业等领域发挥着巨大的作用。一个单一的设备应该有一个处理器，一个无线电和多个传感器。当这些设备在一个领域部署时，传感装置测量这一领域的特殊环境。然后将监测到的数据通过无线电进行传输，再由计算机进行数据分析。这样，无线传感器网络可以对环境中各种变化进行详细的观察。无线传感器网络是能够测量各种现象如在水中的污染物含量，水灌溉流量。比如，最近发生的污染涌流进中国松花江，而松花江又是饮用水的主要来源。通过测定水流量和速度，通过传感器对江水进行实时监测，就能够确定污染桶的数量和流动方向。 不幸的是，人们只是在资源相对丰富这个条件下做文章，无线传感器网络的潜力在很大程度上仍未开发，费用对无线传感器网络是几个主要障碍之一，阻止了其更广阔的发展前景。许多无线传感器网络组件正在趋于便宜化（例如有关计算能力的组件），而传感器本身仍是最昂贵的。正如在在文献[5]中所指出的，成功的技术依赖于
基于FPGA的卡尔曼滤波器的设计
基于FPGA的卡尔曼滤波器的设计 时间：2010-04-12 12:52:33 来源：电子科技作者：米月琴，黄军荣西安电子科技大学摘要：针对电路设计中经常碰到数据的噪声干扰现象，提出了一种Kalman滤波的FPGA实现方法。该方法采用了TI公司的高精度模数转换器ADSl25l以及Altera公司的EPlCl2，首先用卡尔曼滤波算法 设计了一个滤波器，然后将该滤波器分解成简单的加、减、乘、除运算。通过基于FPGA平台的硬件与 软件的合理设计，成功地实现了数据噪声的滤除设计，并通过实践仿真计算，验证了所实现滤波的有效性。 关键词：卡尔曼；FPGA；最小方差估计 卡尔曼滤波是一个“Optimal Recursive Data Processing Algorithm(最优化自回归数据处 理算法)”，对于解决很大部分的问题，是最优化的，效率最高甚至是最有用的。传统的卡尔曼滤波是 在DSP上实现的。但是DSP成本相对较高，而且指令是串行执行的，不能满足有些要求较高的场合。而FPGA由于其硬件结构决定了它的并行处理方式，无论在速度还是实时性都更胜一筹。文中以基于FPGA 器件和A／D转换器的数据采集系统为硬件平台，进行了卡尔曼滤波算法设计，详述了基于FPGA的卡尔 曼滤波器的设计实现。 1 卡尔曼滤波算法 工程中，为了了解工程对象(滤波中称为系统)的各个物理量(滤波中称为状态)的确切数值，或为了 达到对工程对象进行控制的目的，必须利用测量手段对系统的各个状态进行测量。但是，量测值可能仅 是系统的部分状态或是部分状态的线性组合，且量测值中有随机误差(常称为量测噪声)。最优估计就是 针对上述问题的一种解决方法。它能将仅与部分状态有关的测量进行处理，得出从统计意义上讲误差最 小的更多状态的估值。误差最小的标准常称为估计准则，根据不同的估计准则和估计计算方法，有各种 不同的最优估计，卡尔曼滤波是一种递推线性最小方差估计的最优估计。 系统的状态方程可设定为 式（3）为系统噪声。设设备的量测噪声为Vk，系统得量测方程为
IIR数字滤波器的设计外文文献以及翻译
IIR Digita Filter Design An important step in the development of a digital filter is the determination of a realizable transfer function G(z) approximating the given frequency response specifications. If an IIR filter is desired,it is also necessary to ensure that G(z) is stable. The process of deriving the transfer function G(z) is called digital filter design. After G(z) has been obtained, the next step is to realize it in the form of a suitable filter structure. In chapter 8,we outlined a variety of basic structures for the realization of FIR and IIR transfer functions. In this chapter,we consider the IIR digital filter design problem. The design of FIR digital filters is treated in chapter 10. First we review some of the issues associated with the filter design problem. A widely used approach to IIR filter design based on the conversion of a prototype analog transfer function to a digital transfer function is discussed next. Typical design examples are included to illustrate this approach. We then consider the transformation of one type of IIR filter transfer function into another type, which is achieved by replacing the complex variable z by a function of z. Four commonly used transformations are summarized. Finally we consider the computer-aided
电子信息工程外文翻译外文文献英文文献微处理器
外文资料 所译外文资料： 1. 作者G..Bouwhuis, J.Braat, A.Huijser 2. 书名:Principles of Optical Disk Systems 3. 出版时间：1991年9月 4. 所译章节：Session 2/Chapter9, Session 2/Chapter 11 原文： Microprocessor One of the key inventions in the history of electronics, and in fact one of the most important inventions ever period, was the transistor. As time progressed after the inven ti on of LSI in tegrated circuits, the tech no logy improved and chips became smaller, faster and cheaper. The functions performed by a processor were impleme nted using several differe nt logic chips. In tel was the first compa ny to in corporate all of these logic comp onents into a si ngle chip, this was the first microprocessor. A microprocessor is a complete computati on engine that is fabricated on a sin gle chip. A microprocessor executes a collecti on of machi ne in struct ions that tell the processor what to do. Based on the in struct ions, a microprocessor does three basic things: https://www.360docs.net/doc/c217870704.html,ing the ALU (Arithmetic/Logic Unit), a microprocessor can perform mathematical operatio ns like additi on, subtract ion, multiplicatio n and divisi on; 2.A microprocessor can move data from one memory location to another; 3.A microprocessor can make decisi ons and jump to a new set of in struct ions based on those decisi ons. There may be very sophisticated things that a microprocessor does, but those are its three basic activities. Microprocessor has an address bus that sends an address to memory, a data bus that can send data to memory or receive data from memory, an RD(read) and WR(write) line that lets a clock pulse sequenee the processor and a reset li ne that resets the program coun ter to zero(or whatever) and restarts executi on. And let ' s assume that both the address and data buses are 8 bits wide here. Here are the comp onents of this simple microprocessor: 1. Registers A, B and C are simply latches made out of flip-flops. 2. The address latch is just like registers A, B and C. 3. The program coun ter is a latch with the extra ability to in creme nt by 1 whe n told to do so, and also to reset to zero whe n told to do so. 4. The ALU could be as simple as an 8-bit adder, or it might be able to add, subtract, multiply and divide 8- bit values. Let ' s assume the latter here. 5. The test register is a special latch that can hold values from comparisons performed in the ALU. An ALU can normally compare two numbers send determine if they are equal, if one is greater
压力传感器外文翻译
压力传感器 合理进行压力传感器的误差补偿是其应用的关键。压力传感器主要有偏移量误差、灵敏度误差、线性误差和滞后误差，本文将介绍这四种误差产生的机理和对测试结果的影响，同时将介绍为提高测量精度的压力标定方法以及应用实例。 目前市场上传感器种类丰富多样，这使得设计工程师可以选择系统所需的压力传感器。这些传感器既包括最基本的变换器，也包括更为复杂的带有片上电路的高集成度传感器。由于存在这些差异，设计工程师必须尽可能够补偿压力传感器的测量误差，这是保证传感器满足设计和应用要求的重要步骤。在某些情况下，补偿还能提高传感器在应用中的整体性能。 本文以摩托罗拉公司的压力传感器为例，所涉及的概念适用于各种压力传感器的设计应用。 摩托罗拉公司生产的主流压力传感器是一种单片压阻器件，该器件具有 3 类： 1.基本的或未加补偿标定； 2.有标定并进行温度补偿； 3.有标定、补偿和放大。 偏移量、范围标定以及温度补偿均可以通过薄膜电阻网络实现，这种薄膜电阻网络在封装过程中采用激光修正。 该传感器通常与微控制器结合使用，而微控制器的嵌入软件本身建立了传感器数学模型。微控制器读取了输出电压后，通过模数转换器的变换，该模型可以将电压量转换为压力测量值。传感器最简单的数学模型即为传递函数。该模型可在整个标定过程中进行优化，并且模型的成熟度将随标定点的增加而增加。 从计量学的角度看，测量误差具有相当严格的定义：它表征了测量压力与实际压力之间的差异。而通常无法直接得到实际压力，但可以通过采用适当的压力标准加以估计，计量人员通常采用那些精度比被测设备高出至少 10 倍的仪器作为测量标准。 由于未经标定的系统只能使用典型的灵敏度和偏移值将输出电压转换为压 力，测得的压力将产生如图 1 所示的误差。 这种未经标定的初始误差由以下几个部分组成： a.偏移量误差。由于在整个压力范围内垂直偏移保持恒定，因此变换器扩散和激光调节修正的变化将产生偏移量误差。 b.灵敏度误差，产生误差大小与压力成正比。如果设备的灵敏度高于典型值，灵敏度误差将是压力的递增函数（见图 1）。如果灵敏度低于典型值，那么灵敏度误差将是压力的递减函数。该误差的产生原因在于扩散过程的变化。
维纳最速下降法滤波器卡尔曼滤波器设计及Matlab仿真
信息融合大作业 ——维纳最速下降法滤波器，卡尔曼滤波器设计及Matlab仿真 1.滤波问题浅谈 估计器或滤波器这一术语通常用来称呼一个系统，设计这样的系统是为了从含有噪声的数据中提取人们感兴趣的，接近规定质量的信息。由于这样一个宽目标，估计理论应用于诸如通信、雷达、声纳、导航、地震学、生物医学工程、 金融工程等众多不同的领域。例如，考虑一个数字通信系统，其基本形式由发
射机、信道和接收机连接组成。发射机的作用是把数字源(例如计算机)产生的0、1符号序列组成的消息信号变换成为适合于信道上传送的波形。而由于符号间干扰和噪声的存在，信道输出端收到的信号是含有噪声的或失真的发送信号。接收机的作用是，操作接收信号并把原消息信号的一个可靠估值传递给系统输出端的某个用户。随着通信系统复杂度的提高，对原消息信号的还原成为通信系统中最为重要的环节，而噪声是接收端需要排除的最主要的干扰，人们也设计出了针对各种不同条件应用的滤波器，其中最速下降算法是一种古老的最优化技术，而卡尔曼滤波器随着应用条件的精简成为了普适性的高效滤波器。2．维纳最速下降算法滤波器 2.1 最速下降算法的基本思想 考虑一个代价函数，它是某个未知向量的连续可微分函数。函数 将的元素映射为实数。这里，我们要寻找一个最优解。使它满足如下条件 (2.1) 这也是无约束最优化的数学表示。 特别适合于自适应滤波的一类无约束最优化算法基于局部迭代下降的算法： 从某一初始猜想出发，产生一系列权向量，使得代价函数在算法的每一次迭代都是下降的，即 其中是权向量的过去值，而是其更新值。 我们希望算法最终收敛到最优值。迭代下降的一种简单形式是最速下降法，该方法是沿最速下降方向连续调整权向量。为方便起见，我们将梯度向量表示为
数字滤波器的外文翻译
FIR 数字滤波器的有限字长系数优化的比较研究 拜彻尔，泰勒，罗兰 威尔士大学纽波特学院运算工程学校 摘要：实时数字滤波器频率响应的精度受实现时系数约束条件即有限字长(FWL)的影响。该文仅考虑FIR 数字滤波器有关的FWL 问题。准确和近似响应之间的最大误差限的约束条件所对应的理论问题和统计误差值都进行了详细的研究。利用实数值遗传算法作为优化工具，并由若干设计案例的FWL 效应获得其最大误差限和误差值。由此，完成了简单凑整逼近、遗传算法优化、整数规划法，以及简单希尔登山者方法之间的比较。 关键词：实时数字滤波器； 有限字长；遗传算法；整数规划 1. 前言 FIR 数字滤波器广泛用于图像处理、移动通信、医疗电子，以及很多其他的信号处理应用。为降低能耗和提高运算量，截断系数到最短长度是有优势的。然而，该截断会引起滤波嚣设计参数的变化，在某些情况下这是不可接收的。此即优化问题，即尽可能地选择近似系数值的微小变化量，以便最好的服从设计规范标准。针对有限脉冲响应(FIR)滤波器形式结构的线性相位已被证明是鲁棒的，因而FWL 系数的自我实现的研究是极具有吸引力的[1]。FWL FIR 对称数字滤波器的研究涉及到一组系数的选择，从而这个新频率响应可以作为无限准确系数截断的一个结果，可以最大的接近所给定的规范频率响应。 已知的为解决该问题所使用的算法均基于两种方法：局部搜索法[2]和整数规划分支界限法[3,4]。局部搜索法需要选择一组可行的FWL 系数(称为四舍五入值)，用以给出一个频率响应并用以检验H 的领域。同时要选定滤波器的传递函数，以便得到更好的滤波器H'，即具有低误差函数的滤波器。如果找到了这样的一个滤波器H'，那么便可用H'来代替H ，而算法即可进入下一步或者终止。分支界限算法涉及对一组可能解所构成的树的系统性修正，这些解依赖于由枚举总数所确定的下界值。这两种算法本质上计算密集，且不能保证全局优化。其问题即是在于进一步复合，使其更加灵敏以便增加滤波器长度。 2. FWL 系数及误差目标函数 用以导出FWL 系数的最常用定点算法是直接量化法。使用标准滤波器设计技术导出的高精度系数在该方法中首次被利用，以得出FWL 的量化系数。如下量化系数的起始解给出。 h ri =round[h ei 2B-1] i=0,1,2,...,N-1 (1) 这里，h ri 为四舍五入系数，hei 为高精度系数，B 为用以描述系数的位数，N 为滤波器长度。 优化过程的主要目的在于极小化目标函数，其明确目标为获得一个与期望的响应尽可能接近的滤波器频率响应。目标函数被用于500个等距频率的格点。 目标函数通过以下式来评价： }H max ,H 110max{max }H H 1{ObjV s p s s p p i i L s i 2 i P i 2 i -++-=∑∑== (2) H ip =遗传算法优化滤波器在通带中对应频率的幅值响应 H is =遗传算法优化滤波器在阻带中对应频率的幅值响应 L=频率格点的数目（500）
传感器外文翻译
Basic knowledge of transducers A transducer is a device which converts the quantity being measured into an optical, mechanical, or-more commonly-electrical signal. The energy-conversion process that takes place is referred to as transduction. Transducers are classified according to the transduction principle involved and the form of the measured. Thus a resistance transducer for measuring displacement is classified as a resistance displacement transducer. Other classification examples are pressure bellows, force diaphragm, pressure flapper-nozzle, and so on. 1、Transducer Elements Although there are exception ,most transducers consist of a sensing element and a conversion or control element. For example, diaphragms,bellows,strain tubes and rings, bourdon tubes, and cantilevers are sensing elements which respond to changes in pressure or force and convert these physical quantities into a displacement. This displacement may then be used to change an electrical parameter such as voltage, resistance, capacitance, or inductance. Such combination of mechanical and electrical elements form electromechanical transducing devices or transducers. Similar combination can be made for other energy input such as thermal. Photo, magnetic and chemical,giving thermoelectric, photoelectric,electromaanetic, and electrochemical transducers respectively. 2、Transducer Sensitivity The relationship between the measured and the transducer output signal is usually obtained by calibration tests and is referred to as the transducer sensitivity K1= output-signal increment / measured increment . In practice, the transducer sensitivity is usually known, and, by measuring the output signal, the input quantity is determined from input= output-signal increment / K1. 3、Characteristics of an Ideal Transducer The high transducer should exhibit the following characteristics a) high fidelity-the transducer output waveform shape be a faithful reproduction of the measured; there should be minimum distortion. b) There should be minimum interference with the quantity being measured; the presence of the transducer should not alter the measured in any way. c) Size. The transducer must be capable of being placed exactly where it is needed.
直流电机运行状态的卡尔曼滤波估计器设计.doc
二 〇 一 五 年 六 月 题 目：直流电机运行状态的卡尔曼滤波估计器设计 学生姓名：张傲 学 院：电力学院 系 别：电力系 专 业：风能与动力工程 班 级：风能11-1 指导教师：董朝轶 教授
摘要 卡尔曼滤波是一个迭代自回归算法，对于连续运动状态用中的大部分问题它都能够给出最优的预测。它已经广泛应用了近半个世纪，例如数据的融合，机械的导航乃至军用雷达的导航等等。卡尔曼滤波一般用于动态数据的处理，是从混沌的信号中提取有用信号消除误差的参数估计法。卡尔曼滤波是依据上一个估计数值和当下的检测数据运用递推估计算出当前的估计值。通过状态方程运用递推的方法进行估计,可以建立物体运动的模型。本文采用的工程设计对运行状态下的直流电机进行参数的计算和校验。而且直流电机的调节性能非常好只需要加上电阻调压就可以了，而且启动曲线非常好，启动的转矩大适合高精度的控制。而交流电机调速需要变频，控制相对复杂一些，而对于设计无论是哪种电机都不影响结果，所以本实验采用直流电机。简单来说卡尔曼滤波就是对被观测量进行一个物理的建模，目的是用‘道理’来约束观测结果，减少噪声的影响。因此卡尔曼滤波是根据一个事物的当前状态预测它的下一个状态的过程。 此设计主要是通过对直流电机的数学模型利用MATLAB来设计卡尔曼滤波估计，进行仿真编程建模，进而对系统进行评估，并且分析估计误差。 关键词：卡尔曼滤波器；直流电机；MATLAB
Abstract Kalman filter is an iterative autoregression algorithm for continuous motion of most of the problems with it are able to give the best prediction. And it has been widely used for nearly half a century, such as the integration of data, as well as military machinery of navigation radar navigation, and so on. Kalman filter is generally used to process dynamic data, extract useful signal parameter estimation method to eliminate errors from the chaotic signal. Kalman filter is based on an estimate on the value and the current detection data is calculated using recursive estimation current estimates. By using recursive state equation method to estimate the movement of objects can be modeled. The paper describes the engineering design of the DC motor running state parameter calculation and verification. The DC motor performance and adjust very well simply by adding resistance regulator on it, and start curve is very good, start torque for precision control. The required frequency AC motor speed control is relatively complicated, and for the design of either the motor does not affect the outcome.In order to facilitate learning, so wo use the DC motor. Simply the Kalman filter is to be observables conduct a physical modeling; the purpose is to use 'sense' to restrict the observations to reduce the influence of noise. Therefore, the Kalman filter is based on the current state of things predict its next state of the process. This design is mainly through the DC motor mathematical model using MATLAB to design the Kalman filter estimation, simulation modeling program, and then to evaluate the system and analyze the estimation error. Keywords：Kalman filter; DC;MATLAB
传感器技术外文文献及中文翻译
Sensor technology A sensor is a device which produces a signal in response to its detecting or measuring a property ,such as position , force , torque , pressure , temperature , humidity , speed , acceleration , or vibration .Traditionally ,sensors (such as actuators and switches )have been used to set limits on the performance of machines .Common examples are (a) stops on machine tools to restrict work table movements ,(b) pressure and temperature gages with automatics shut-off features , and (c) governors on engines to prevent excessive speed of operation . Sensor technology has become an important aspect of manufacturing processes and systems .It is essential for proper data acquisition and for the monitoring , communication , and computer control of machines and systems . Because they convert one quantity to another , sensors often are referred to as transducers .Analog sensors produce a signal , such as voltage ,which is proportional to the measured quantity .Digital sensors have numeric or digital outputs that can be transferred to computers directly .Analog-to-coverter(ADC) is available for interfacing analog sensors with computers . Classifications of Sensors Sensors that are of interest in manufacturing may be classified generally as follows: Machanical sensors measure such as quantities as positions ,shape ,velocity ,force ,torque , pressure , vibration , strain , and mass . Electrical sensors measure voltage , current , charge , and conductivity . Magnetic sensors measure magnetic field ,flux , and permeablity . Thermal sensors measure temperature , flux ,conductivity , and special heat . Other types are acoustic , ultrasonic , chemical , optical , radiation , laser ,and fiber-optic . Depending on its application , a sensor may consist of metallic , nonmetallic , organic , or inorganic materials , as well as fluids ,gases ,plasmas , or semiconductors .Using the special characteristics of these materials , sensors covert the quantity or property measured to analog or digital output. The operation of an ordinary mercury thermometer , for example , is based on the difference between the thermal expansion of mercury and that of glass. Similarly , a machine part , a physical obstruction , or barrier in a space can be detected by breaking the beam of light when sensed by a photoelectric cell . A proximity sensor ( which senses and measures the distance between it and an object or a moving member of a machine ) can be based on acoustics , magnetism , capacitance , or optics . Other actuators contact the object and take appropriate action ( usually by electromechanical means ) . Sensors are essential to the conduct of intelligent robots , and are being developed with capabilities that resemble those of humans ( smart sensors , see the following ). This is America, the development of such a surgery Lin Bai an example, through the screen, through a remote control operator to control another manipulator, through the realization of the right abdominal surgery A few years ago our country the