数字信号处理英文文献及翻译
数字信号处理(英文版)0-引言
The foundation of information
technology is digitalization. The kernel of digitalization is digital signal processing Most of digital signal processing, especially real-time processing are implemented by DSP processor or ASIC based on DSP core DSP technology becomes hot front edge and is growing up rapidly.
Digital system：By the Nyquist Rule，the
processing speed is limited by the S/H, A/D and processor speed.
We still need analog processing
(3)The most signals in real would are analog. If we want to process these analog signals with digital signal processing system, must change them into digital form first by mixed signal processing.
Digital system：Modify software.
Example：Analog filter, digital
filter, adaptive filter
Why digital?
（2）Precision
南邮专业英语报告 信号处理导论完整版(包含翻译,原文和单词)
0
1
2
SWEEP
样值处理算法来计算飘动的滤波器系数，再分别计算每次输入抽样的滤波。
Flanging、合唱、调相三种效果都是把一个简单滤波器的系数设计尾随输入
抽样变化而使滤波器成为时变滤波器。自适应信号处理也是随时间改变滤波器的
系数。系数与时间之间的关系是受某些设计条件的限制，即滤波器系数相对于输
入抽样调节并且优化。自适应算法的实施也就是要求滤波器的样值处理算法当中
英文原文
8.2 Digital Audio Effects Audio effects, such as delay, echo, reverberation, comb filtering, flanging, chorusing, pitch shifting, stereo imaging, distortion, compression, expansion, noise gating, and equalization, are indispensable in music production and performance [115 –151]. Some are also available for home and car audio systems.
程序chorus.m演示的是正弦信号经合唱处理后的情形。 调相(Phase Shifting)对吉他手、键盘演奏人员、歌唱家来说是经常采用的一种 效果。调相是把声音信号用一个窄带陷状滤波器过滤，再把过滤信号的一部分与 源信号相加而得到的。
陷点的频率以可控的方式调节，比如说可以用一个低频振荡器，也可以用脚踏板 控制。陷点附近的频率有较强的漂移，与原来的直接声音结合，使得相位在频率 轴上发生抵消或加强，整个相位在频率轴上出现波动。
dsp外文翻译
外文参考文献翻译英文题目 The Breadth and Depth of DSP 中文题目 DSP的广度和深度学院自动化与电气工程学院专业自动化姓名白学文学号 201108536指导教师王思明2015 年 04月 20日DSP的广度和深度数字信号处理是最强大的技术，将塑造二十一世纪的科学与工程之一。
革命性的变化已经在广泛的领域：通信，医疗成像，雷达和声纳，高保真音乐再现，石油勘探，仅举几例。
上述各领域已建立了深厚的DSP技术，用自己的算法，数学，和专门技术。
这种呼吸和深度的结合，使得它不可能为任何一个人掌握所有已开发的DSP技术。
DSP教育包含两个任务：学习一般适用于作为一个整体领域的概念，并学习您感兴趣的特定领域的专门技术。
本章开始描述DSP已在几个不同领域的戏剧性效果的数字信号处理的世界，我们的旅程。
革命已经开始。
1 DSP的根源独特的数据类型，它使用的信号，数字信号处理是区别于其他计算机科学领域。
在大多数情况下，这些信号源于感觉来自现实世界的数据：地震的震动，视觉图像，声波等DSP是数学，算法，并用来操纵这些信号的技术后，他们已被转换成数字形式。
这包括了各种目标，如：加强视觉图像识别和语音生成，存储和传输的数据压缩，等假设我们重视计算机模拟 - 数字转换器，并用它来获得一个现实世界的数据块。
DSP回答了这个问题：下一步怎么办？DSP的根是在20世纪60年代和70年代数字计算机时首次面世。
电脑是昂贵的，在这个时代，DSP是有限的，只有少数关键应用。
努力开拓，在四个关键领域：雷达和声纳，国家安全风险是石油勘探，可以大量资金;太空探索，其中的数据是不可替代的;和医疗成像，可节省生活。
20世纪80年代和90年代的个人电脑革命，引起新的应用DSP的爆炸。
而不是由军方和政府的需求动机，DSP的突然被带动的商业市场。
任何人士如认为他们可以使资金在迅速扩大的领域突然一个DSP供应商。
DSP的市民等产品达到：移动电话机，光盘播放器，电子语音邮件。
(完整版)数字信号处理英文文献及翻译
数字信号处理一、导论数字信号处理（DSP）是由一系列的数字或符号来表示这些信号的处理的过程的。
数字信号处理与模拟信号处理属于信号处理领域。
DSP包括子域的音频和语音信号处理，雷达和声纳信号处理，传感器阵列处理，谱估计，统计信号处理，数字图像处理，通信信号处理，生物医学信号处理，地震数据处理等。
由于DSP的目标通常是对连续的真实世界的模拟信号进行测量或滤波，第一步通常是通过使用一个模拟到数字的转换器将信号从模拟信号转化到数字信号。
通常，所需的输出信号却是一个模拟输出信号，因此这就需要一个数字到模拟的转换器。
即使这个过程比模拟处理更复杂的和而且具有离散值，由于数字信号处理的错误检测和校正不易受噪声影响，它的稳定性使得它优于许多模拟信号处理的应用（虽然不是全部）。
DSP算法一直是运行在标准的计算机，被称为数字信号处理器（DSP）的专用处理器或在专用硬件如特殊应用集成电路（ASIC）。
目前有用于数字信号处理的附加技术包括更强大的通用微处理器，现场可编程门阵列（FPGA），数字信号控制器（大多为工业应用，如电机控制）和流处理器和其他相关技术。
在数字信号处理过程中，工程师通常研究数字信号的以下领域：时间域（一维信号），空间域（多维信号），频率域，域和小波域的自相关。
他们选择在哪个领域过程中的一个信号，做一个明智的猜测（或通过尝试不同的可能性）作为该域的最佳代表的信号的本质特征。
从测量装置对样品序列产生一个时间或空间域表示，而离散傅立叶变换产生的频谱的频率域信息。
自相关的定义是互相关的信号本身在不同时间间隔的时间或空间的相关情况。
二、信号采样随着计算机的应用越来越多地使用，数字信号处理的需要也增加了。
为了在计算机上使用一个模拟信号的计算机，它上面必须使用模拟到数字的转换器（ADC）使其数字化。
采样通常分两阶段进行，离散化和量化。
在离散化阶段，信号的空间被划分成等价类和量化是通过一组有限的具有代表性的信号值来代替信号近似值。
数字信号处理的翻译
- 一个网页浏览器软件
- 一个播放软件，支持wav声音格式
- 一个播放软件，支持AVI视频格式
2。要查看此CD的内容，请打开
INDEX.HTM在网页浏览器中的文件。
3。 “方案”的目录包含几个目录
在这本书的章节中使用的方案，编写和测试下
MATLAB 7.0版本。为方便起见，这些文件已被
此CD包含的补充材料
文字书“数字信号处理：
基于计算机的方法“，第三版。
SK米特拉，ISBN 0073043869。
1。系统要求
- 操作系统：Windows或Linux或Macintosh
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- 显示颜色：16位色或更高
- PDF查看器：与Acrobat Reader浏览
PDF格式的最常用的功能和一些基本概念
与MATLAB。
7。 “常见问题”目录中包含一些常见的答案
其中读者学习本书时可能遇到的的问题。
8。以下的音乐声演示教授柯蒂斯道路和大卫先生Thall提供，
媒体艺术和技术方案，美国加州大学圣巴巴拉分校。
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信号处理中英文对照外文翻译文献
信号处理中英文对照外文翻译文献(文档含英文原文和中文翻译)译文：一小波研究的意义与背景在实际应用中，针对不同性质的信号和干扰，寻找最佳的处理方法降低噪声，一直是信号处理领域广泛讨论的重要问题。
目前有很多方法可用于信号降噪，如中值滤波，低通滤波，傅立叶变换等，但它们都滤掉了信号细节中的有用部分。
传统的信号去噪方法以信号的平稳性为前提，仅从时域或频域分别给出统计平均结果。
根据有效信号的时域或频域特性去除噪声，而不能同时兼顾信号在时域和频域的局部和全貌。
更多的实践证明，经典的方法基于傅里叶变换的滤波，并不能对非平稳信号进行有效的分析和处理，去噪效果已不能很好地满足工程应用发展的要求。
常用的硬阈值法则和软阈值法则采用设置高频小波系数为零的方法从信号中滤除噪声。
实践证明，这些小波阈值去噪方法具有近似优化特性，在非平稳信号领域中具有良好表现。
小波理论是在傅立叶变换和短时傅立叶变换的基础上发展起来的，它具有多分辨分析的特点，在时域和频域上都具有表征信号局部特征的能力，是信号时频分析的优良工具。
小波变换具有多分辨性、时频局部化特性及计算的快速性等属性，这使得小波变换在地球物理领域有着广泛的应用。
随着技术的发展，小波包分析(Wavelet Packet Analysis)方法产生并发展起来，小波包分析是小波分析的拓展，具有十分广泛的应用价值。
它能够为信号提供一种更加精细的分析方法，它将频带进行多层次划分，对离散小波变换没有细分的高频部分进一步分析，并能够根据被分析信号的特征，自适应选择相应的频带，使之与信号匹配，从而提高了时频分辨率。
小波包分析(wavelet packet analysis)能够为信号提供一种更加精细的分析方法，它将频带进行多层次划分，对小波分析没有细分的高频部分进一步分解，并能够根据被分析信号的特征，自适应地选择相应频带,使之与信号频谱相匹配，因而小波包具有更广泛的应用价值。
利用小波包分析进行信号降噪，一种直观而有效的小波包去噪方法就是直接对小波包分解系数取阈值，选择相关的滤波因子，利用保留下来的系数进行信号的重构，最终达到降噪的目的。
数字信号处理(英文版)1-连续时间信号系统
Unit impulse function δ(t)
With a gate signal pτ(t), short the duration τ and keep the unit area
4/τ 2/τ 1/τ
1/τ
-τ/2
τ/2
-τ/4
τ/4
-τ/8 τ/8
When τ0, the amplitude tends to , which means it is impossible to define δ(t) by a regular function.
Typical signals and their representation
Gate signal
p (t ) 0
1
|t |
2
1 -τ/2 τ/2
|t |
2
The gate signal can be represented by unit step signals:
(t )dt (t )dt (t )dt u (t )
0
0
Properties of δ(t)
δ(t) is a even function, that is
δ(t) = δ(-t) We got δ(t) from a gate signal, and gate signal is an even function. It is also easy to give the math show of the even property.
Typical signals and their representation
Sinusoidal Asin(ωt+υ)
数字信号处理英文文献及翻译
英文原文The simulation and the realization of the digital filterWith the information age and the advent of the digital world, digital signal processing has become one of today's most important disciplines and door technology. Digital signal processing in communications, voice, images, automatic control, radar, military, aerospace, medical and household appliances, and many other fields widely applied. In the digital signal processing applications, the digital filter is important and has been widely applied.1、 figures Unit on :Analog and digital filtersIn signal processing, the function of a filter is to remove unwanted parts of the signal, such as random noise, or to extract useful parts of the signal, such as the components lying within a certain frequency range.The following block diagram illustrates the basic idea.There are two main kinds of filter, analog and digital. They are quitedifferent in their physical makeup and in how they work. An analog filter uses analog electronic circuits made up from components such as resistors, capacitors and op amps to produce the required filtering effect. Such filter circuits are widely used in such applications as noise reduction, video signal enhancement, graphic equalisers in hi-fi systems, and many other areas. There are well-established standard techniques for designing an analog filter circuit for a given requirement. At all stages, the signal being filtered is an electrical voltage or current which is the direct analogue of the physical quantity (e.g. a sound or video signal or transducer output) involved. Adigital filter uses a digital processor to perform numerical calculations on sampled values of the signal. The processor may be a general-purpose computersuch as a PC, or a specialised DSP (Digital Signal Processor) chip. The analog input signal must first be sampled and digitised using an ADC (analog todigital converter). The resulting binary numbers, representing successive sampled values of the input signal, are transferred to theprocessor, which carries out numerical calculations on them. These calculations typically involve multiplying the input values by constants and adding the products together. If necessary, the results of these calculations, which now represent sampled values of the filtered signal, are output through a DAC (digital to analog converter) to convert the signal back to analog form.Note that in a digital filter, the signal is represented by a sequence of numbers, rather than a voltage or current.The following diagram shows the basic setup of such a system.Unit refers to the input signals used to filter hardware or software. If the filter input, output signals are separated, they are bound to respond to the impact of the Unit is separated, such as digital filters filter definition. Digital filter function, which was to import sequences X transformation into export operations through a series Y.According to figures filter function 24-hour live response characteristics, digital filters can be divided into two, namely, unlimited long live long live the corresponding IIR filter and the limited response to FIR filters. IIRfilters have the advantage of the digital filter design can use simulation results, and simulation filter design of a large number of tables mayfacilitate simple. It is the shortcomings of the nonlinear phase; Linear phase if required, will use the entire network phase-correction. Image processing and transmission of data collection is required with linear phase filters identity. And FIR linear phase digital filter to achieve, but an arbitrary margincharacteristics. Impact from the digital filter response of the units can be divided into two broad categories : the impact of the limited response (FIR) filters, and unlimited number ofshocks to (IIR) digital filters.FIR filters can be strictly linear phase, but because the system FIR filter function extremity fixed at the original point, it can only use the higher number of bands to achieve their high selectivity for the same filter design indicators FIR filter called band than a few high-IIR 5-10 times, the cost is higher, Signal delay is also larger. But if the same linear phase, IIR filters must be network-wide calibration phase, the same section also increase the number of filters and network complexity. FIR filters can be used to achieve non-Digui way, not in a limited precision of a shock, and into the homes and quantitative factors of uncertainty arising from the impact of errors than IIR filter small number, and FIR filter can be used FFT algorithms, the computational speed. But unlike IIR filter can filter through the simulation results, there is no ready-made formula FIR filter must use computer-aided design software (such as MATLAB) to calculate. So, a broader application of FIR filters, and IIR filters are not very strict requirements on occasions.Unit from sub-functions can be divided into the following four categories :(1) Low-filter (LPF);(2) high-filter (HPF);(3) belt-filter (BPF);(4) to prevent filter (BSF).The following chart dotted line for the ideals of the filter frequency characteristics :A1(f) A2(f)10 c2f c2 f(a) (b)A3(f) A4(f)0 c1c2f c1c2 f(c) (d)(a)LPF (b)HPF (c)BPF (d)BSF2、 MATLAB introducedMATLAB is a matrix laboratory (Matrix Laboratory) is intended. In addition to an excellent value calculation capability, it also provides professional symbols terms, word processing, visualization modeling, simulation and real-time control functions. MATLAB as the world's top mathematical software applications, with a strong engineering computing, algorithms research, engineering drawings, applications development, data analysis and dynamic simulation, and other functions, in aerospace, mechanical manufacturing and construction fields playing an increasingly important role. And the C language function rich, the use of flexibility, high-efficiency goals procedures. High language both advantages as well as low level language features. Therefore, C language is the most widely used programming language. Although MATLAB is a complete, fully functional programming environment, but in some cases, data and procedures with the external environment of the world is very necessary and useful. Filter design using Matlab, could be adjusted with the design requirements and filter characteristics of the parameters, visual simple, greatly reducing the workload for the filter design optimization.In the electricity system protection and secondary computer control, many signal processing and analysis are based on are certain types Yeroskipou and the second harmonics of the system voltage and current signals (especially at D process), are mixed with a variety of complex components, the filter has been installed power system during the critical components. Current computer protection and the introduction of two digital signal processing software main filter. Digital filter design using traditional cumbersome formula, the need to change the parameters after recalculation, especially in high filters, filter design workload. Uses MATLAB signal processing boxes can achieve rapid and effective digital filter design and simulation.MATLAB is the basic unit of data matrix, with its directives Biaodashi mathematics, engineering, commonly used form is very similar, it is used to solve a problem than in MATLAB C, Fortran and other languages End precision much the same thing. The popular MATLAB 5.3/Simulink3.0 including hundreds of internal function with the main pack and 30 types of tool kits (Toolbox). kits can be divided into functional tool kits and disciplines toolkit. MATLAB tool kit used to expand the functional symbols terms, visualization simulation modelling, word processing and real-time control functions. professional disciplines toolkit is a stronger tool kits, tool kits control, signal processing tool kit, tool kits, etc. belonging to such communicationsMATLAB users to open widely welcomed. In addition to the internal function, all the packages MATLAB tool kits are readable document and the document could be amended, modified or users through Yuanchengxu the construction of new procedures to prepare themselves for kits.3、 Digital filter designDigital filter design of the basic requirementsDigital filter design must go through three steps :(1) Identification of indicators : In the design of a filter, there must be some indicators. These indicators should be determined on the basis of the application. In many practical applications, digital filters are often used to achieve the frequency operation. Therefore, indicators in the form of general jurisdiction given frequency range and phase response. Margins key indicators given in two ways. The first is absolute indicators. It provides a function to respond to the demands of the general application of FIR filter design. The second indicator is the relative indicators. Its value in the form of answers to decibels. In engineering practice, the most popular of such indicators. For phase response indicators forms, usually in the hope that the system with a linear phase frequency bands human. Using linear phase filter design with thefollowing response to the indicators strengths：①it only contains a few algorithms, no plural operations；②there is delay distortion, only a fixed amount of delay; ③the filter length N (number of bands for N-1), the volume calculation for N/2 magnitude.(2) Model approach : Once identified indicators can use a previous study of the basic principles and relationships, a filter model to be closer to the target system.(3) Achieved : the results of the above two filters, usually by differential equations, system function or pulse response to describe. According to this description of hardware or software used to achieve it.4、 Introduced FPGA Programmable logic device is a generic logic can use a variety of chips, which is to achieve ASIC ASIC (Application Specific Integrated Circuit) semi-customized device, Its emergence and development of electronic systems designers use CAD tools to design their own laboratory in the ASIC device. Especially FPGA (Field Programmable Gate Array) generated and development, as a microprocessor, memory, the figures for electronic system design and set a new industry standard (that is based on standard product sales catalogue in the market to buy). Is a digital system for microprocessors, memories, FPGA or three standard building blocks constitute their integration direction.Digital circuit design using FPGA devices, can not only simplify the design process and can reduce the size and cost of the entire system, increasing system reliability. They do not need to spend the traditional sense a lot of time and effort required to create integrated circuits, to avoid the investment risk and become the fastest-growing industries of electronic devices group. Digital circuit design system FPGA devices using the following main advantages (1) Design flexibleUse FPGA devices may not in the standard series device logic functional limitations. And changes in system design and the use of logic in any one stage of the process, and only through the use of re-programming the FPGA device can be completed, the system design provides for great flexibility.(2) Increased functional densityFunctional density in a given space refers to the number of functional integration logic. Programmable logic chip components doors several high, a FPGA can replace several films, film scores or even hundreds of small-scale digital IC chip illustrated in the film. FPGA devices using the chip to use digital systems in small numbers, thus reducing the number of chips used to reduce the number of printed size and printed, and will ultimately lead to a reduction in the overall size of the system.(3) Improve reliabilityPrinting plates and reduce the number of chips, not only can reduce system size, but it greatly enhanced system reliability. A higher degree ofintegration than systems in many low-standard integration components for the design of the same system, with much higher reliability. FPGA device used to reduce the number of chips required to achieve the system in the number printed on the cord and joints are reduced, the reliability of the system can be improved.(4) Shortening the design cycleAs FPGA devices and the programmable flexibility, use it to design a system for longer than traditional methods greatly shortened. FPGA device master degrees high, use printed circuit layout wiring simple. At the same time, success in the prototype design, the development of advanced tools, a high degree of automation, their logic is very simple changes quickly. Therefore, the use of FPGA devices can significantly shorten the design cycle system, and speed up the pace of product into the market, improving product competitiveness.(5) Work fastFPGA/CPLD devices work fast, generally can reach several original Hertz, far larger than the DSP device. At the same time, the use of FPGA devices, the system needed to achieve circuitclasses and small, and thus the pace of work of the entire system will be improved.(6) Increased system performance confidentialityMany FPGA devices have encryption functions in the system widely used FPGA devices can effectively prevent illegal copying products were others(7) To reduce costsFPGA device used to achieve digital system design, if only device itself into the price, sometimes you would not know it advantages, but there are many factors affecting the cost of the system, taken together, the cost advantages of using FPGA is obvious. First, the use of FPGA devices designed to facilitate change, shorten design cycles, reduce development costs for system development; Secondly, the size and FPGA devices allow automation needs plug-ins, reducing the manufacturing system to lower costs; Again, the use of FPGA devices can enhance system reliability, reduced maintenance workload, thereby lowering the cost of maintenance services for the system. In short, the use of FPGA devices for system design to save costs.FPGA design principles :FPGA design an important guiding principles : the balance and size and speed of exchange, the principles behind the design of the filter expression of a large number of certification.Here, "area" means a design exertion FPGA/CPLD logic resources of the FPGA can be used to the typical consumption (FF) and the search table (IUT) to measuremore general measure can be used to design logic equivalence occupied by the door is measured. "pace" means stability operations in the chip design can achieve the highest frequency, the frequency of the time series design situation, and design to meet the clock cycle -- PADto pad, Clock Setup Time, Clock Hold Beijing, Clock-to-Output Delay, and other characteristics of many time series closely related. Area (area) and speed (speed) runs through the two targets FPGA design always is the ultimate design quality evaluation criteria. On the size and speed of the two basic concepts : balance of size and speed and size and speed of swap.One pair of size and speed is the unity of opposites contradictions body. Requirements for the design of a design while the smallest, highest frequency of operation is unrealistic. More scientific goal should be to meet the design requirements of the design time series (includes requirements for the design frequency) premise, the smallest chip area occupied. Or in the specified area, the design time series cushion greater frequency run higher. This fully embodies the goals of both size and speed balanced thinking. On the size and speed requirements should not be simply interpreted as raising the level and design engineers perfect sexual pursuit, and should recognize that they are products and the quality and cost of direct relevance. If time series cushion larger design, running relatively high frequency, that the design Jianzhuangxing stronger, more quality assurance system as a whole; On the other hand, the smaller size of consumption design is meant to achieve in chip unit more functional modules, the chip needs fewer, the entire system has been significantly reduced cost. As a contradiction of the two components, the size and speed is not the same status. In contrast, meet the timetables and work is more important for some frequency when both conflicts, the use of priority guidelines.Area and the exchange rate is an important FPGA design ideas. Theoretically, if a design time series cushion larger, can run much higher than the frequency design requirements, then we can through the use of functional modules toreduce the consumption of the entire chip design area, which is used for space savings advantages of speed; Conversely, if the design of a time series demanding, less than ordinary methods of design frequency then generally flow through the string and data conversion, parallel reproduction of operational module, designed to take on the whole "string and conversion" and operate in the export module to chip in the data "and string conversion" from the macro point of view the whole chip meets the requirements of processing speed, which is equivalent to the area of reproduction - rate increase.For example. Assuming that the digital signal processing system is 350Mb/s input data flow rate, and in FPGA design, data processing modules for maximum processing speed of 150Mb/s, because the data throughput processing module failed to meet requirements, it is impossible to achieve directly in the FPGA. Such circumstances, they should use "area-velocity" thinking, at least three processing modules from the first data sets will be imported and converted, and then use these three modules parallel processing of data distribution, then the results "and string conversion," we have complete data rate requirements. We look at both ends of the processing modules, data rate is 350Mb/s, and in view of the internal FPGA, each sub-module handles the data rate is 150Mb/s, in fact, all the data throughput is dependent on three security modules parallel processing subsidiary completed, that is used by more chip area achieve high-speed processing through "the area of reproduction for processing speed enhancement" and achieved design.FPGA is the English abbreviation Field of Programmable Gate Array for the site programmable gate array, which is in Pal, Gal, Epld, programmable device basis to further develop the product. It is as ASIC (ASIC) in the field of a semi-customized circuit and the emergence of both a customized solution to the shortage circuit, but overcome the original programmable devices doors circuit few limited shortcomings.FPGA logic module array adopted home (Logic Cell Array), a new concept of internal logic modules may include CLB (Configurable Logic Block), export import module IOB (Input Output Block) and internal links (Interconnect) 3. FPGA basic features are :(1) Using FPGA ASIC design ASIC using FPGA circuits, the chip can be used,while users do not need to vote films production.(2) FPGA do other customized or semi-customized ASIC circuits throughout the Chinese specimen films.3) FPGA internal capability and rich I/O Yinjue.4) FPGA is the ASIC design cycle, the shortest circuit, the lowest development costs, risks among the smallest device5) FPGA using high-speed Chmos crafts, low consumption, with CMOS, TTL low-power compatibleIt can be said that the FPGA chip is for small-scale systems to improve system integration, reliability one of the bestCurrently FPGA many varieties, the Revenue software series, TI companies TPC series, the fiex ALTERA company series FPGA is stored in films from theinternal RAM procedures for the establishment of the state of its work, therefore, need to programmed the internal Ram. Depending on the different configuration, users can use a different programming methodsPlus electricity, FPGA, EPROM chips will be read into the film, programming RAM 中 data, configuration is completed, FPGA into working order. Diaodian, FPGA resume into white films, the internal logic of relations disappear, FPGA to repeated use. FPGA's programming is dedicated FPGA programming tool, using generic EPROM, prom programming device can. When the need to modify functional FPGA, EPROM can only change is. Thus, with a FPGA, different programming datato produce different circuit functions. Therefore, the use of FPGA very flexible.There are a variety of FPGA model : the main model for a parallel FPGA plus a EPROM manner; From the model can support a number of films FPGA; serial prom programming model could be used serial prom FPGA programming FPGA; The external model can be engineered as microprocessors from its programming microprocessors.Verilog HDL is a hardware description language for the algorithm level, doors at the level of abstract level to switch-level digital system design modelling. Modelling of the target figure by the complexity of the system can be something simple doors and integrity of electronic digital systems. Digital system to the levels described, and in the same manner described in Hin-time series modelling.Verilog HDL language with the following description of capacity : design behaviour characteristics, design data flow characteristics, composition and structure designed to control and contain the transmission and waveform design a certification mechanism. All this with the use of a modelling language. In addition, Verilog HDL language programming language interface provided by the interface in simulation, design certification from the external design of the visit, including specific simulation control and operation.Verilog HDL language grammar is not only a definition, but the definition of each grammar structure are clear simulation, simulation exercises. Therefore, the use of such language to use Verilog simulation models prepared by a certification. From the C programming language, the language inherited multiple operating sites and structures. Verilog HDL provides modelling capacity expansion, many of the initial expansion would be difficult to understand. However, the core subsets of Verilog HDL language very easy to learn and use, which is sufficient for most modelling applications. Of course, the integrityof the hardware description language is the most complex chips from theintegrity of the electronic systems described.historyVerilog HDL language initially in 1983 by Gateway Design Automation companies for product development simulator hardware modelling language. Then it is only a dedicated language. Since their simulation, simulation devices widely used products, Verilog HDL as a user-friendly and practical language for many designers gradually accepted. In an effort to increase the popularity of the language activities, Verilog HDL language in 1990 was a public area. Open Verilog International (OVI) is to promote the development of Verilog international organizations. 1992, decided to promote OVI OVI standards as IEEE Verilog standards. The effort will ultimately succeed, a IEEE1995 Verilog language standard, known as IEEE Std 1364-1995. Integrity standards in Verilog hardware description language reference manual contains a detailed description.Main capacity：Listed below are the main Verilog hardware description language ability*Basic logic gate, and, for example, or have embedded in the language and nand * Users of the original definition of the term (UDP), the flexibility. Users can be defined in the original language combinations logic original language, the original language of logic could also be time series* Switches class infrastructure models, such as the nmos and pmos also be embedded in the language* Hin-language structure designated for the cost of printing the design and trails Shi Shi and design time series checks.* Available three different ways to design or mixed mode modelling. These methods include : acts described ways - use process of structural modelling; Data flow approach - use of a modelling approach Fuzhi expression; Structured way - using examples of words to describe modular doors and modelling.* Verilog HDL has two types of data : data types and sequence data line network types. Line network types that the physical links between components and sequence types that abstract data storage components.* To describe the level design, the structure can be used to describe any level module example * Design size can be arbitrary; Language is design size (size) impose any restrictions* Verilog HDL is no longer the exclusive language of certain companies but IEEE standards. * And the machine can read Verilog language, it may as EDA tools and languages of the world between the designers* Verilog HDL language to describe capacity through the use of programming language interface (PLI) mechanism further expansion. PLI is to allow external functions of the visit Verilog module information, allowing designers and simulator world Licheng assembly* Design to be described at a number of levels, from the switch level, doors level, register transfer level (RTL) to the algorithm level, including thelevel of process and content* To use embedded switching level of the original language in class switch design integrity modelling* Same language can be used to generate simulated incentive and certification by the designated testing conditions, such as the value of imports of the designated*Verilog HDL simulation to monitor the implementation of certification, the certification process of implementing the simulation can be designed to monitorand demonstrate value. These values can be used to compare with the expectations that are not matched in the case of print news reports.* Acts described in the class, not only in the RTL level Verilog HDL design description, and to describe their level architecture design algorithm level behavioural description* Examples can use doors and modular structure of language in a class structure described* Verilog HDL mixed mode modelling capabilities in the design of a different design in each module can level modelling* Verilog HDL has built-in logic function, such as*Structure of high-level programming languages, such as conditions of expression, and the cycle of expression language, language can be used* To it and can display regular modelling* Provide a powerful document literacy* Language in the specific circumstances of non-certainty that in the simulator, different models can produce different results; For example, describing events in the standard sequence of events is not defined.5、In troduction of DSPToday, DSP is w idely used in the modern techno logy and it has been the key part of many p roducts and p layed more and mo re impo rtant ro le in our daily life.Recent ly, Northw estern Po lytechnica lUniversity Aviation Microelect ronic Center has comp leted the design of digital signal signal p rocesso r co re NDSP25, w h ich is aim ing at TM S320C25 digital signal p rocesso r of Texas Inst rument TM S320 series. By using top 2dow n design flow , NDSP25 is compat ible w ith inst ruct ion and interface t im ing of TM S320C25.Digital signal processors (DSP) is a fit for real-time digital signal processing for high-speed dedicated processors, the main variety used for real-time digital signal processing to achieve rapid algorithms. In today's digital age background, the DSP has become the communications, computer, and consumer electronics products, and other fields based device.Digital signal processors and digital signal processing is inseparably, we usually say "DSP" can also mean the digital signal processing (Digital Signal Processing), is that in this digital signal processors Lane. Digital signal processing is a cover many disciplines applied to many areas and disciplines, refers to the use of computers or specialized processing equipment, the signals in digital form for the collection, conversion, recovery, valuation, enhancement, compression, identification, processing, the signals are compliant form. Digital signal processors for digital signal processing devices, it is accompanied by a digital signal processing to produce. DSP development process is broadly divided into three phases : the 20th century to the 1970s theorythat the 1980s and 1990s for the development of products. Before the emergence of the digital signal processing in the DSP can only rely on microprocessors (MPU) to complete. However, the advantage of lower high-speed real-time processing can not meet the requirements. Therefore, until the 1970s, a talent made based DSP theory and algorithms. With LSI technology development in 1982 was the first recipient of the world gave birth to the DSP chip. Years later, the second generation based on CMOS工艺 DSP chips have emerged. The late1980s, the advent of the third generation of DSP chips. DSP is the fastest-growing 1990s, there have been four successive five-generation and the generation DSP devices. After 20 years of development, the application of DSP products has been extended to people's learning, work and all aspects of life and gradually become electronics products determinants.中文翻译。
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数字信号处理一、导论数字信号处理（DSP）是由一系列的数字或符号来表示这些信号的处理的过程的。
数字信号处理与模拟信号处理属于信号处理领域。
DSP包括子域的音频和语音信号处理，雷达和声纳信号处理，传感器阵列处理，谱估计，统计信号处理，数字图像处理，通信信号处理，生物医学信号处理，地震数据处理等。
由于DSP的目标通常是对连续的真实世界的模拟信号进行测量或滤波，第一步通常是通过使用一个模拟到数字的转换器将信号从模拟信号转化到数字信号。
通常，所需的输出信号却是一个模拟输出信号，因此这就需要一个数字到模拟的转换器。
即使这个过程比模拟处理更复杂的和而且具有离散值，由于数字信号处理的错误检测和校正不易受噪声影响，它的稳定性使得它优于许多模拟信号处理的应用（虽然不是全部）。
DSP算法一直是运行在标准的计算机，被称为数字信号处理器（DSP）的专用处理器或在专用硬件如特殊应用集成电路（ASIC）。
目前有用于数字信号处理的附加技术包括更强大的通用微处理器，现场可编程门阵列（FPGA），数字信号控制器（大多为工业应用，如电机控制）和流处理器和其他相关技术。
在数字信号处理过程中，工程师通常研究数字信号的以下领域：时间域（一维信号），空间域（多维信号），频率域，域和小波域的自相关。
他们选择在哪个领域过程中的一个信号，做一个明智的猜测（或通过尝试不同的可能性）作为该域的最佳代表的信号的本质特征。
从测量装置对样品序列产生一个时间或空间域表示，而离散傅立叶变换产生的频谱的频率域信息。
自相关的定义是互相关的信号本身在不同时间间隔的时间或空间的相关情况。
二、信号采样随着计算机的应用越来越多地使用，数字信号处理的需要也增加了。
为了在计算机上使用一个模拟信号的计算机，它上面必须使用模拟到数字的转换器（ADC）使其数字化。
采样通常分两阶段进行，离散化和量化。
在离散化阶段，信号的空间被划分成等价类和量化是通过一组有限的具有代表性的信号值来代替信号近似值。
奈奎斯特-香农采样定理指出，如果样本的取样频率大于两倍的信号的最高频率，一个信号可以准确地重建它的样本。
在实践中，采样频率往往大大超过所需的带宽的两倍。
数字模拟转换器（DAC）用于将数字信号转化到模拟信号。
数字计算机的使用是数字控制系统中的一个关键因素。
三、时间域和空间域在时间或空间域中最常见的处理方法是对输入信号进行一种称为滤波的操作。
滤波通常包括对一些周边样本的输入或输出信号电流采样进行一些改造。
现在有各种不同的方法来表征的滤波器，例如：一个线性滤波器的输入样本的线性变换；其他的过滤器都是“非线性”。
线性滤波器满足叠加条件，即如果一个输入不同的信号的加权线性组合，输出的是一个同样加权线性组合所对应的输出信号。
“因果”滤波器只使用以前的样本的输入或输出信号；而“非因果”滤波器使用未来的输入样本。
一个非因果滤波器通常可以通过增加一个延迟将它变成了一个因果滤波器。
“时间不变”滤波器随着时间的推移性具有稳定特性；其他滤波器如随时间变化的自适应滤波器。
一些滤波器是“稳定”的，别的是“不稳定的”。
一个稳定的滤波器产生的输出信号随时间收敛于一个恒定值，或在一个有限的时间间隔内是有界的。
一种不稳定的滤波器可以产生一个没有增长界限的输出，甚至零输入有界。
“有限脉冲响应（FIR）”滤波器只使用于输入信号，而“无限脉冲响应滤波器（IIR）”使用于输入信号和输出信号之前的样品。
FIR滤波器总是稳定的，而IIR滤波器可能是不稳定的。
大多数滤波器可以被描述在z域（频域的一个超集）的传递函数。
如果它是一个FIR滤波器的脉冲响应和阶跃响应，滤波器也可以被描述为一个差分方程，或对零点和极点的收集。
一个FIR滤波器的输出是通过对任何给定的输入与脉冲响应的卷积计算得到的。
滤波器也可以被用来推导出一个样品的处理算法的方块图利用硬件指令实现滤波器所代表。
四、频域信号通常是通过傅立叶变换将其从时间或空间域转换到频率域。
傅里叶变换将信号转换信息和相位分量级的每个频率。
通常的傅里叶变换转换为功率谱，这是大小的每个频率分量的平方。
在频域对信号分析的最常见的用途是信号特性分析。
工程师可以研究频谱来确定哪一频率的存在于输入信号中。
滤波，特别是在非实时的工作也可以被转换到频域实现，应用滤波器，然后转换回时域。
这是一个快速，O（nlogn）操作，可以基本上给出任何滤波器的形状包括砖墙滤波器优良的逼近。
有一些常用的频域变换。
例如，倒谱转换信号的频域傅立叶变换，取对数，然后将另一个傅里叶变换。
这强调的频率成分的幅度较小而保留的频率分量的大小顺序。
频域分析又称谱或谱分析。
五、信号处理信号通常需要以不同的方式进行处理。
例如，从一个传感器的输出信号可能被污染的多余电“噪音”。
电极连接到一个病人的胸部时，心电图是测量由心脏和其他肌肉的活动引起的微小的电压变化。
由于电的干扰从电源的强烈影响，信号通常是采用“总管拾取”。
处理信号的滤波电路可以消除或至少降低信号的不需要的部分。
现在，越来越多的的情况下，是由DSP技术来进行信号的滤波以提高信号质量或提取重要信息，而不是模拟电子技术。
六、DSP的发展数字信号处理的发展从1960年代的大型数字计算机的数字运算应用程序的使用快速傅立叶变换（FFT），它允许一个信号的频谱可以快速计算。
这些技术在当时没有被广泛使用，因为合适的计算设备通常仅在大学及其他科研机构可以使用。
七、数字信号处理器（DSP）在20世纪70年代末和20世纪80年代初微处理机的介绍使DSP技术在更广泛的范围内得到了使用。
然而，通用微处理器如Intel x86的家庭并不适合于DSP的计算密集型的需求，随着20世纪80年代DSP重要性的增加导致几个主要的电子产品制造商（如德克萨斯仪器，模拟设备和摩托罗拉）去开发数字信号处理器芯片，专门的微处理器，专门设计用于在数字信号处理要求的操作的类型的架构。
（注意，缩写DSP数字信号处理的不同的意思，这个词用于处理数字信号，多种技术或数字信号处理器，一种特殊类型的微处理器芯片）。
像一个通用微处理器，DSP是一种具有其自己的本地指令代码的可编程器件。
DSP芯片是能够每秒进行数以百万计的浮点运算，像他们同类型的更著名的通用器件，更快和更强大的版本正在不断被引入。
DSP也可以嵌入在复杂的“系统芯片”装置，通常包括模拟和数字电路。
8、数字信号处理器的应用DSP技术是当今普遍在手机，多媒体计算机，录像机，CD播放器，硬盘驱动器和控制器的调制解调器等设备，并将很快在电视和电话业务中取代模拟电路。
DSP的一个重要的应用是信号的压缩和解压。
信号压缩用于数字蜂窝电话，在每一个地方的“单元”让更多的电话同时被处理。
DSP信号压缩技术不仅使人们可以相互交谈，而且可以通过使用安装在计算机上的小的摄像机使人们通过显示器看见对方，而这些只需要将传统的电话线连接在一起。
在音频CD 系统，DSP技术来执行复杂的错误检测和校正原始数据，因为它是从光盘读取。
虽然一些潜在的DSP技术的数学理论，如傅立叶和希尔伯特变换，数字滤波器的设计和信号压缩，可以相当复杂，而数值运算所需的实际实现这些技术是非常简单的，主要包括操作可以在一个便宜的四功能的计算器上进行操作。
一种DSP芯片的结构设计进行这样的操作非常快，处理的样品每秒数以亿计，提供实时的性能：即，能够处理一个实时的信号，因为它是采样，然后输出信号的处理，例如扬声器或视频显示。
所有的DSP应用前面提到的实例，如硬盘驱动器和移动电话，要求实时操作。
主要电子产品制造商已投入巨资在DSP技术。
因为他们现在发现在大众市场的产品应用中，DSP芯片的电子装置占有世界市场的很大比例。
销售额每年数十亿美元，并可能继续快速增长。
DSP主要应用的音频信号处理，音频压缩，数字图像处理，视频压缩，语音处理，语音识别，数字通信，雷达，声纳，地震，和生物医学。
具体的例子是在数字移动电话的语音压缩与传输，空间匹配均衡的音响、扩声领域，良好的天气预测，经济预测，地震数据处理，和工业过程控制分析，计算机生成的动画电影中，医学影像如CAT扫描和MRI，MP3压缩，图像处理，高保真度扬声器分频器和均衡，并与电吉他放大器使用的音频效果。
九、数字信号处理的实验数字信号处理是经常使用专门的微处理器，如dsp56000，TMS320，或SHARC。
这些通常处理数据使用定点运算，虽然某些版本可以使用浮点算法和更强大。
更快的应用FPGA可能从慢启动流处理器应用Freescale公司的出现，传统的较慢的处理器如单片机可能是适当的。
【英文原文】Digital Signal Processing1、IntroductionDigital signal processing (DSP) is concerned with the representation of the signals by a sequence of numbers or symbols and the processing of these signals. Digital signal processing and analog signal processing are subfields of signal processing. DSP includes subfields like audio and speech signal processing, sonar and radar signal processing, sensor array processing, spectral estimation, statistical signal processing, digital image processing, signal processing for communications, biomedical signal processing, seismic data processing, etc.Since the goal of DSP is usually to measure or filter continuous real-world analog signals, the first step is usually to convert the signal from an analog to a digital form, by using an analog to digital converter. Often, the required output signal is another analog output signal, which requires a digital to analog converter. Even if this process is more complex than analog processing and has a discrete value range, the stability of digital signal processing thanks to error detection and correction and being less vulnerable to noise makes it advantageous over analog signal processing for many, though not all, applications.DSP algorithms have long been run on standard computers, on specialized processors called digital signal processors (DSP)s, or on purpose-built hardware such as application-specific integrated circuit (ASICs). Today there are additional technologies used for digital signal processing including more powerful general purpose microprocessors, field-programmable gate arrays (FPGAs), digital signal controllers (mostly for industrial applications such as motor control), and stream processors, among others.In DSP, engineers usually study digital signals in one of the following domains: time domain (one-dimensional signals), spatial domain (multidimensional signals), frequency domain, autocorrelation domain, and wavelet domains. They choose the domain in which to process a signal by making an informed guess (or by trying different possibilities) as to which domain best represents the essential characteristics of the signal. A sequence of samples from a measuring device produces a time or spatial domain representation, whereas a discrete Fourier transform produces the frequency domain information that is the frequency spectrum. Autocorrelation is defined as the cross-correlation of the signal with itself over varying intervals of time or space.2、Signal SamplingWith the increasing use of computers the usage of and need for digital signal processing has increased. In order to use an analog signal on a computer it must be digitized with an analog to digital converter (ADC). Sampling is usually carried out in two stages, discretization and quantization. In the discretization stage, the space of signals is partitioned into equivalence classes and quantization is carried out by replace the signal with representative signal values are approximated by values from a finite set.The Nyquist-Shannon sampling theorem states that a signal can be exactly reconstructed from its samples if the samples if the sampling frequency is greater than twice the highest frequency of the signal. In practice, the sampling frequency is often significantly more than twice the required bandwidth.A digital to analog converter (DAC) is used to convert the digital signal back to analog signal. The use of a digital computer is a key ingredient in digital control systems.3 、Time and Space DomainsThe most common processing approach in the time or space domain is enhancement of the input signal through a method called filtering. Filtering generally consists of some transformation of a number of surrounding samples around the current sample of the input or output signal. There are various ways to characterize filters, for example: A “linear” filter is a linear transformation of input samples; other filters are “non-linear.” Linear filters satisfy the superposition condition, i.e. if an input is a weighted linear combination of different signals, the output is an equally weighted linear combination of the corresponding output signals.A “causal”filter uses only previous samples of the input or output signals; while a “non-causal” filter uses future input samples. A non-causal filter can usually be changed into a causal filter by adding a delay to it.A “time-invariant”filter has constant properties over time; other filters such as adaptive filters change in time.Some filters are “stable”, others are “unstable”. A stable filter produces an output that converges to a constant value with time, or remains bounded within a finite interval. An converges to a constant value with time, or remains bounded within a finite interval. An unstable filter can produce an output that grows without bounds, with bounded or even zero input.A “Finite Impulse Response”(FIR) filter uses only the input signal, while an “Infinite Impulse Response” filter (IIR) uses both the input signal and previous samples of the output signal. FIR filters are always stable, while IIR filters may be unstable.Most filters can be described in Z-domain (a superset of the frequency domain) by their transfer functions. A filter may also be described as a difference equation, a collection of zeroes and poles or, if it is an FIR filter, an impulse response or step response. The output of an FIR filter to any given input may be calculated by convolving the input signal with the impulse response. Filters can also be represented by block diagrams which can then be used to derive a sample processing algorithm to implement the filter using hardware instructions.4、Frequency DomainSignals are converted from time or space domain to the frequency domain usually through the Fourier transform. The Fourier transform converts the signal information to a magnitude and phase component of each frequency. Often the Fourier transform is converted to the power spectrum, which is the magnitude of each frequency component squared.The most common purpose for analysis of signals in the frequency domain is analysis of signal properties. The engineer can study the spectrum to determine which frequencies are present in the input signal and which are missing.Filtering, particularly in non real-time work can also be achieved by converting to the frequency domain, applying the filter and then converting back to the time domain. This is a fast, O (n log n) operation, and can give essentially any filter shape including excellent approximations to brickwall filters.There are some commonly used frequency domain transformations. For example, the cepstrum converts a signal to the frequency domain Fourier transform, takes the logarithm, then applies another Fourier transform. This emphasizes the frequency components with smaller magnitude while retaining the order of magnitudes of frequency components. Frequency domainanalysis is also called spectrum or spectral analysis.5、Signal ProcessingSignals commonly need to be processed in a variety of ways. For example, the output signal from a transducer may well be contaminated with unwanted electrical “noise”. The electrodes attached to a patient’s chest when an ECG is taken measure tiny electrical voltage changes due to the activity of the heart and other muscles. The signal is often strongly affected by “mains pickup” due to electrical interference from the mains supply. Processing the signal using a filter circuit can remove or at least reduce the unwanted part of the signal. Increasingly nowadays, the filtering of signals to improve signal quality or to extract important information is done by DSP techniques rather than by analog electronics.6、Development of DSPThe development of digital signal processing dates from the 1960’s with the use of mainframe digital computers number-crunching applications such an the Fast Fourier Transform (FFT), which allows the frequency spectrum of a signal to be computed rapidly. These techniques are not widely used at that time, because suitable computing equipment was generally available only in universities and other scientific research institutions.7、Digital Signal Processors (DSPs)The introduction of the microprocessor in the late 1970’s and early 1980’s made it possible for DSP techniques to be used in a much wider range of applications. However, general-purpose microprocessors such as the Inter x86 family are not ideally suited to the numerically-intensive requirements of DSP, and during the 1980’s the increasing importance of DSP led several major electronics manufacturers (such as Texas Instruments, Analog Devices and Motorola) to develop Digital Signal Processor chips-specialised microprocessors with architectures designed specifically for the types of operations required in digital signal processing.(Note that the acronym DSP can variously mean Digital Signal Processing, the term used for a wide range of techniques for processing signals digitally, or Digital Signal Processor, a specialized type of microprocessor chip). Like a general-purpose microprocessor, a DSP is a programmable device, with its own native instruction code. DSP chip are capable of carrying out millions of floating point operations per second, and like their better-known general-purpose cousins, faster and more powerful versions are continually being introduced. DSPs can also be embedded within complex “system-on-chip” devices, often containing both analog and digital circuitry.8、Applications of DSPDSP technology is nowadays commonplace in such devices as mobile phones, multimedia computers, video recorders, CD players, hard disc drive controllers and modems, and will soon replace analog circuitry in TV sets and telephones. An important application of DSP is in signal compression and decompression. Signal compression is used in digital cellular phones to allow a greater number of calls to be handled simultaneously within each local “cell”. DSP signal compression technology allows people not only to talk to one another but also to see one anther on their computer screens, using small video cameras mounted on the computer monitors, with only a conventional telephone line linking them together. In audio CD systems, DSP technology is used to perform complex error detection and correction on the raw data as it is read from the CD.Although some of the mathematical theory underlying DSP techniques, such as Fourier and Hilbert transforms, digital filter design and signal compression, can be fairly complex, the numerical operations required actually to implement these techniques are very simple, consistingmainly of operations that could be done on a cheap four-function calculator. The architecture of a DSP chip is designed to carry out such operations incredibly fast, processing hundreds of millions of samples every second, to provided real-time performance: that is , the ability to process a signal “live” as it is sampled and then output the processed signal, for example to a loudspeaker or video display. All of the practical examples of DSP applications mentioned earlier, such as hard disc drives and mobile phones, demand real-time operation.The major electronics manufacturers have invested heavily in DSP technology. Because they now find application in mass-market products, DSP chips account for a substantial proportion of the world market for electronic devices. Sales amount to billions of dollars annually, and seem likely to continue to increase rapidly.The main applications of DSP are audio signal processing, audio compression, digital image processing, video compression, speech processing, speech recognition, digital communications, RADAR, SONAR, seismology, and biomedicine. Specific examples are speech compression and transmission in digital mobile phones, room matching equalization of sound in hi-fi and sound reinforcement applications, weather forecasting, economic forecasting, seismic data processing, analysis and control of industrial processes, computer-generated animations in movies, medical imaging such as CAT scans and MRI, MP3 compression, image manipulation, high fidelity loudspeaker crossovers and equalization, and audio effects for use with electric guitar amplifiers.9、ImplementationDigital signal processing is often implemented using specialized microprocessors such as the DSP56000, the TMS320, or the SHARC. These often process data using fixed-point arithmetic, although some versions are available which use floating point arithmetic and are more powerful. For faster applications FPGAs might be emerge from companies including Freescale and startup Stream Processors Inc. For slow applications, a traditional slower processor such as a microcontroller may be adequate.。