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1、Digital Signal Processing- System Anlysis and Design,Digital Signal Processing System Anlysis and Design,作译者：Paulo S.R.Diniz等著 ISBN号：7-5053-8171-7/TN.1702 电子工业出版社 中译本：门爱东等译，ISBN号：7-121-00063-6（2004-7）,Digital Signal Processing,Chapter 1 Discrete-time system,4,digital,Of, relating to, or resembling a
2、 digit, especially a finger. 手指的：手指的、与手指有关的或类似手指的 Operated or done with the fingers: 用手指操作或工作的： a digital switch.数字开关 Having digits. 有手指、足趾的 Expressed in digits, especially for use by a computer. 数字的：用数字表示，尤其用在计算机上 Using or giving a reading in digits: 计数的：使用或读出均为数字形式： a digital clock.数字式钟,5,Signal-,
3、An indicator, such as a gesture or colored light, that serves as a means of communication.See Synonyms at gesture 信号：一种用作通讯交流手段的指示，比如一种手势或有色的光参见 gesture A message communicated by such means. 信号：用这种手段传达的信息 Electronics An impulse or a fluctuating electric quantity, such as voltage, current, or electri
4、c field strength, whose variations represent coded information. 【电子学】 电波：电脉冲或变化的电量，比如电压、电流或电场强度，它们的变化表示着编码后的信息 The sound, image, or message transmitted or received in telegraphy, telephony, radio, television, or radar. 信号：由电报、电话、收音机、电视机或雷达传播或收到的声音、影像或信息,6,process,To put through the steps of a prescr
5、ibed procedure: 处理，进行：使通过一系列预定程序的各项步骤： processing newly arrived immigrants; received the order, processed it, and dispatched the goods.接待新到的移民；接到订单，进行处理，然后发送货物 To prepare, treat, or convert by subjecting to a special process: 调制，加工处理：通过特殊程序准备、处理或转换： process ore to obtain minerals.加工矿石获取矿物质 Computer
6、Science To perform operations on (data). 【计算机科学】 处理，进程：执行对（数据）的操作,7,system,A group of interacting, interrelated, or interdependent elements forming a complex whole. 系统：组成一个复杂的整体的一组互相作用、互相联系或互相依存的元素 A functionally related group of elements, especially: 系统：一组在功能上互相联系的元素，尤指： The human body regarded as
7、a functional physiological unit. 身体系统：作为一个生理功能单位的人的身体 An organism as a whole, especially with regard to its vital processes or functions. 有机体系统：作为一个整体的有机体，尤指当与它的重要变化过程或作用有关时 A group of physiologically or anatomically complementary organs or parts: 系统：一组生理或结构上互补器官或部分： the nervous system; the skeletal
8、 system.神经系统；骨骼系统 A group of interacting mechanical or electrical components. 装置：一组相互作用的机械或电子部件 A network of structures and channels, as for communication, travel, or distribution. 设施：由组织与频道组成的网状系统，如为通讯，旅行或发行而设的,8,1.1 Introduction,The world of science and engineering is filled with signals: images f
9、rom remote space probes, voltages generated by the heart and brain, radar and sonar echoes, Seismic地震 vibrations, countless other applications.,9,1.1 Introduction,Digital Signal Processing is the science of using computers to understand these types of data. This includes a wide variety of goals: fil
10、tering, speech recognition, image enhancement, data compression, neural networks, and much more.,10,Digital Signal Processing (DSP) is used in a wide variety of applications.,11,DSP is one of the most powerful technologies that will shape science and engineering in the twenty-first century. Suppose
11、we attach an analog-to-digital converter to a computer, and then use it to acquire a chunk of real world data. DSP answers the question: What next?,12,good reasons for learning DSP,Its the future! Think how electronics has changed the world in the last 50 years. DSP will have the same role over the
12、next 50 years. Learn it or be left behind! DSP can snatch success from the jaws of failure Let Steve Smith tell you about some examples from his own career. Excellent graphics- figures, graphs, and illustrations,13,a great example of how DSP can improve the understandability of data,a problem relate
13、d to shading in the images. Preliminary measurements had shown that the perimeter of the image would be darker than the center. This is caused by several effects: how the image area is scanned, the way x-rays backscatter from the body, the detector characteristics, etc. the center is too bright, whi
14、le the border is too dark,14,a great example of how DSP can improve the understandability of data.,Digital filtering was able to convert the raw image (on the left) into a processed image (on the right). This is The processed image contains the same information as the raw image, but in a form tailor
15、ed to the characteristics of the human visual system. The improvement is obvious; look at the buckles on the shoes, the ring on the finger, and the simulated explosive on the chest,15,A simple CT system,passes a narrow beam of x- rays through the body from source to detector. The source and detector
16、 are then translated to obtain a complete view. The remaining views are obtained by rotating the source and detector in about 1 degree increments, and repeating the translation process.,16,Computed tomography image,. This is a CT slice of a human abdomen, at the level of the navel. Many organs are v
17、isible, such as the (L) Liver, (K) Kidney, (A) Aorta, (S) Spine, and (C) Cyst covering the right kidney. CT can visualize internal anatomy far better than conventional medical x-rays.,17,Compact disc playback block diagram,The digital information is retrieved from the disc with an optical sensor, co
18、rrected for EFM and Reed-Solomon encoding, and converted to stereo analog signals.,18,Deconvolution of old phonograph recordings,The frequency spectrum produced by the original singer (a). Resonance peaks in the primitive equipment, (b), produce distortion in the recorded frequency spectrum, (c). Th
19、e frequency response of the deconvolution filter, (d), is designed to counteracts the undesired convolution, restoring the original spectrum, for illustrative purposes only; not actual signals.,19,The human retina视网膜,. The retina contains three principle layers: (1) the rod and cone light receptors,
20、 (2) an intermediate layer for data reduction and image processing, and (3) the optic nerve fibers that lead to the brain. The structure of these layers is seemingly backward, requiring light to pass through the other layers before reaching the light receptors.,20,Human speech model,Over a short seg
21、ment of time, about 2 to 40 milliseconds, speech can be modeled by three parameters: (1) the selection of either a periodic or a noise excitation, (2) the pitch of the periodic excitation, and (3) the coefficients of a recursive linear filter mimicking the vocal tract response.,21,Binary skeletoniza
22、tion. The binary image of a fingerprint,(a), contains ridges that are many pixels wide. The skeletonized version, (b), contains ridges only a single pixel wide.,22,3x3 edge modification,The original image, (a), was acquired on an airport x-ray baggage scanner. The shift and subtract operation, shown
23、 in (b), results in a pseudo three-dimensional effect.,23,good reasons for learning DSP,A three step approach in explaining concepts Explain the concept in words; present the mathematics; show how it is used in a computer program. If one doesnt make sense, maybe the other two will help. Simple compu
24、ter programs Look at these example programs . Digital Filters: simple to implement, incredible performance! Check out these examples.,24,Single pole low-pass filter.,Digital recursive filters can mimic analog filters composed of resistors and capacitors. As shown in this example, a single pole low-p
25、ass recursive filter smoothes the edge of a step input, just as an electronic RC filter.,25,Common point spread functions,. The pillbox, Gaussian, and square, shown in (a), (b), & (c), are common smoothing (low-pass) filters. Edge enhancement (high-pass) filters are formed by subtracting a low-pass
26、kernel from an impulse, as shown in (d). The sinc function, (e), is used very little in image processing because images have their information encoded in the spatial domain, not the frequency domain.,26,Common point spread functions,27,Chebyshev frequency responses,. Figures (a) and (b) show the fre
27、quency responses of low-pass Chebyshev filters with 0.5% ripple, while (c) and (d) show the corresponding high-pass filter responses.,28,Execution times for calculating the DFT,The correlation method refers to the algorithm described in Table. This method can be made faster by precalculating the sin
28、e and cosine values and storing them in a look-up table (LUT). The FFT (Table 12-3) is the fastest algorithm when the DFT is greater than 16 points long. The times shown are for a Pentium processor at 100 MHz.,29,good reasons for learning DSP,Delayed use of complex numbers Most books on DSP are fill
29、ed with complex math. We try to explain all the important techniques using only basic algebra. .and the best reason for learning DSP: Your competition knows DSP Jobs, promotions, grant money, product sales; we are all in competition. Up-to-date technologies can make the difference- and DSP is one of
30、 most powerful!,30,the future of DSP education,To understand the future of DSP education, think about another technology: electronics. If this is your main field, you probably took dozens of classes on the subject; everything from the operation of transistors to the internal design of integrated cir
31、cuits. However, if electronics is not your specialty, your education will have been very different. You probably took one or two classes in applied electronics. You learned Nyquist law, the design of simple filters, and other practical techniques. You know nothing about electron-hole physics in semi
32、conductors, and you dont care! You use electronics as a tool to further your research or design activities. For every expert in electronics, there are 100 scientists and engineers that have a basic familiarly with the practical applications. This is the future of DSP.,31,Examples of Digital Filters,
33、Digital filters are incredibly powerful, but easy to use. In fact, this is one of the main reasons that DSP has become so popular. As an example, suppose we need a low-pass filter at 1 kHz. This could be carried out in analog electronics with the following circuit: :,32,For instance, this might be u
34、sed for noise reduction or separating multiplexed signals. As an alternative, we could digitize the signal and use a digital filter. Say we sample the signal at 10 kHz. A comparable digital filter is carried out by the following program:,33,Low-pass windowed-sinc filter,%This program filters 5000 sa
35、mples with a 101 point windowed-sinc filter, resulting in 4900 samples of filtered data. X= ; %X holds the input signal %Y holds the output signal;H holds the filter kernel % PI = 3.14159265 FC = 0.1; %The cutoff frequency (0.1 of the sampling rate) M= 100 %The filter kernel length %CALCULATE THE FI
36、LTER KERNEL FOR I= 1:101 IF (I-M/2) = 0 THEN H(I)= 2*PI*FC; ELSE H(I) = SIN(2*PI*FC * (I-M/2) / (I-M/2); END H(I) = H(I) * (0.54 - 0.46*COS(2*PI*I/M) ) ; END,34,%FILTER THE SIGNAL BY CONVOLUTION FOR J = 101:5000 Y(J) = 0; FOR I = 1: 101 Y(J) = Y(J) + X(J-I) * H(I) END END,35,As in this example, most
37、 digital filters can be implemented with only a few dozen lines of code. How do the analog and digital filters compare? Here are the frequency responses of the two filters:,36,several significant differences between the AF and DF,Even though we designed the digital filter to approximately match the
38、analog filter First, the analog filter has a 6% ripple in the passband, while the digital filter is perfectly flat (within 0.02%). The analog designer might argue that the ripple can be selected in the design; however, this misses the point. The flatness achievable with analog filters is limited by
39、the accuracy of their resistors and capacitors. Even if it is designed for zero ripple (a Butterworth filter), analog filters of this complexity will have a residue ripple of, perhaps, 1%. On the other hand, the flatness of digital filters is primarily limited by round-off error, making them hundred
40、s of times flatter than their analog counterparts.,37,several significant differences between the AF and DF,Next, lets look at the frequency response on a log scale (decibels), as shown below. Again, the digital filter is clearly the victor in both roll-off and stopband attenuation .,38,Even if the
41、analog performance is improved by adding additional stages, it still cant compete with the digital filter. Imagine you need to improve the performance of the filter by a factor of 100. This would be virtually impossible for the analog circuit, but only requires simple modifications to the digital fi
42、lter. For instance, look at the two frequency responses below, a digital filter designed for very fast roll-off, and a digital filter designed for exceptional stopband attenuation.,39,The frequency response on the left has a gain of 1 +/- 0.0002 from DC to 999 hertz, and a gain of less than 0.0002 f
43、or frequencies above 1001 hertz. The entire transition occurs in only about 1 hertz. The frequency response on the right is equally impressive: the stopband attenuation is -150 dB, one part in 30 million! Dont try this with an op amp! As in these examples, digital filters can achieve thousands of ti
44、mes better performance than analog filters. This makes a dramatic difference in how filtering problems are approached. With analog filters, the emphasis is on handling limitations of the electronics, such as the accuracy and stability of the resistors and capacitors. In comparison, digital filters a
45、re so good that the performance of the filter is frequently ignored. The emphasis shifts to the limitations of the signals, and the theoretical issues regarding their processing.,40,another example of the tremendous power of digital filters.,Filters usually have one of four basic responses: low-pass
46、, high-pass, band-pass or band-reject. But what if you need something really custom? As an extreme example, suppose you need a filter with the frequency response shown at the right. This isnt as far fetched as you might think; several area of DSP routinely use frequency responses this irregular (dec
47、onvolution and optimal filtering). Dont ask an analog filter designer to give you this frequency response- he cant! In comparison, digital filters excel at providing these irregular curves.,41,A stability problem in the analog-to-digital converter for 0.1% precision,it was only an 8 bit device, inca
48、pable of achieving 0.1% precision. more severe, the analog-to-digital conversion was trashed with noise. As shown on the left below, the digital output randomly toggled over about a dozen digital numbers. The system should have been designed with 12 bits; it was designed with 8 bits; but it operated
49、 with only about 5 bits of usable data. As any good electrical engineer would, our first step was to plaster the ADC with capacitors. No luck- the noise was coming from high current pulses in the ground plane of the electrical panel- very difficult to solve. Two months minimum to redesign the problem areas. What a mess.,42,43,DSP for solving,First, the fancy explanation: we used a multirate technique. The original system sampled at 100 samples per second. We increased the sampling rate to 100,000 samples per second, and then used a