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1、 畢業(yè)設(shè)計(jì)(論文)外文資料翻譯 系 ： 電子信息系 專(zhuān) 業(yè)： 電子信息科學(xué)與技術(shù) 姓 名： 學(xué) 號(hào)： 外文出處： DSP Design Line,Techonline Community, By Dr Iain A. Robin 附 件：1.外文資料翻譯譯文；2.外文原文 指導(dǎo)教師

2、評(píng)語(yǔ)： 簽名： 年 月 日 附件1：外文資料翻譯譯文 數(shù)字濾波器簡(jiǎn)介 模擬和數(shù)字濾波器 在信號(hào)處理過(guò)程中，濾波器的功能是去除信號(hào)中不需要的部分，如隨機(jī)噪聲，或者是提取信號(hào)中有用的部分，如包含在一定頻率范圍內(nèi)的有用信號(hào)。 下面的框圖表明了這一基本觀點(diǎn)： 濾波器有兩種主要的類(lèi)型：模擬濾波器和數(shù)字濾波器。他們的物質(zhì)組成和工作原理都

3、是完全不同的。 模擬濾波器是由模擬電子電路組成的，如電阻、電感和運(yùn)算放大器來(lái)產(chǎn)生所需的過(guò)濾效果。這樣的濾波器電路被廣泛應(yīng)用在噪聲的降低、視頻信號(hào)的增強(qiáng)、音響系統(tǒng)中的圖像均衡以及其他的多個(gè)領(lǐng)域中。目前已經(jīng)有很完善的技術(shù)標(biāo)準(zhǔn)來(lái)滿(mǎn)足一個(gè)已經(jīng)提出要求的模擬濾波器電路的設(shè)計(jì)。在各個(gè)階段，過(guò)濾信號(hào)就是一個(gè)有物理量參與并且直接被模擬的電壓或電流量。 一個(gè)數(shù)字濾波器使用數(shù)字處理器來(lái)執(zhí)行信號(hào)的采樣值的數(shù)值計(jì)算。該處理器可以是通用計(jì)算機(jī)，如PC機(jī)（個(gè)人電腦）或者是一個(gè)專(zhuān)用的數(shù)字信號(hào)處理芯片。 模擬輸入信號(hào)必須先使用一個(gè)ADC（模擬到數(shù)字轉(zhuǎn)換器）采樣和數(shù)字化。由此產(chǎn)生代表連續(xù)采樣輸入信號(hào)值的二進(jìn)制數(shù)字，是轉(zhuǎn)移

4、到能夠?qū)λ鼈冞M(jìn)行數(shù)值處理器上。這些計(jì)算通常都涉及乘以由常量與輸入信號(hào)相加的最終輸入值。如果需要，這些現(xiàn)在代表采樣的信號(hào)值濾波結(jié)果的計(jì)算，是由一個(gè)DAC（數(shù)字到模擬轉(zhuǎn)換器）輸出的信號(hào)轉(zhuǎn)換回模擬形式。 請(qǐng)注意，在數(shù)字濾波中，信號(hào)是由一組數(shù)字序列，而不是電壓或電流。 下圖顯示了一個(gè)這樣系統(tǒng)的基本設(shè)置： 使用數(shù)字濾波器的優(yōu)點(diǎn) 下面的列表給出了數(shù)字比模擬濾波器的一些主要優(yōu)點(diǎn)： 1. 數(shù)字濾波器是可編程的，即它的操作決定與其存儲(chǔ)在處理器內(nèi)存中的程序。這就意味著數(shù)字濾波器在不影響電路（硬件）的前提下可以很容易的被改變。模擬濾波器只能通過(guò)重新設(shè)計(jì)濾波器硬件電路來(lái)改變； 2. 數(shù)字濾波器很容

5、易設(shè)計(jì)，測(cè)試以及實(shí)行于通用計(jì)算機(jī)或工作站中； 3. 模擬濾波電路的特點(diǎn)（特別是那些含有不穩(wěn)定性元件）受溫度漂移的影響并且依賴(lài)于溫度。而數(shù)字濾波器不受制于這些問(wèn)題，因此對(duì)于溫度和時(shí)間，它極其的穩(wěn)定； 4. 跟模擬濾波器不同，數(shù)字過(guò)濾器可以準(zhǔn)確地處理低頻信號(hào)；隨著技術(shù)的DSP的速度繼續(xù)增加，數(shù)字過(guò)濾器被應(yīng)用到高頻信號(hào)的RF（射頻）領(lǐng)域，這個(gè)在過(guò)去曾經(jīng)是模擬技術(shù)專(zhuān)有的； 5. 數(shù)字濾波器是非常靈活，他們具有以不同的方式來(lái)處理信號(hào)能力，這其中包括一些典型數(shù)字濾波器能夠適應(yīng)信號(hào)按其特點(diǎn)變化而變化的能力； 6. DSP處理器可以快速處理一系列由并聯(lián)或串聯(lián)級(jí)的等復(fù)雜組合的過(guò)濾器，與等效的模擬

6、電路相比較，這使得硬件要求相對(duì)簡(jiǎn)單、緊湊。 數(shù)字濾波器的操作 在本節(jié)中，我們將介紹數(shù)字濾波器運(yùn)行的基本理論。這對(duì)于理解如何設(shè)計(jì)和使用數(shù)字濾波器是一個(gè)必不可少的。 假設(shè)被數(shù)字化的“原始”信號(hào)以電壓波形的時(shí)間函數(shù)來(lái)描述： V = x(t) 其中t代表時(shí)間。 這個(gè)信號(hào)是以時(shí)間間隔h（采樣間隔）進(jìn)行采樣的。其第i個(gè)信號(hào)的采樣值是時(shí)間t = i*h的函數(shù)： x i = x ( ih ) 因此由ADC至處理器轉(zhuǎn)換來(lái)的數(shù)字值就由下列的數(shù)字序列表示： x0 , x1 , x2 , x3 , ... 信號(hào)的波形值與時(shí)間相對(duì)應(yīng)： t = 0, h, 2h, 3h, ... 并且當(dāng)

7、t = 0時(shí)，開(kāi)始采樣。 在時(shí)間t = nh（其中n是正整數(shù)），將值 x0 , x1 , x2 , x3 , ... x n 提供給處理器，并存儲(chǔ)在內(nèi)存中。 注意，采樣值xn+1, xn+2等是不可用的，因?yàn)樗麄冞€不存在。 y0 , y1 , y2 , y3 , ... y n 通常來(lái)說(shuō)，數(shù)值y n是由x序列計(jì)算得到的。由y序列得到x序列的算法決定于具體的數(shù)字濾波器。 在下一節(jié)，我們將看看一些簡(jiǎn)單數(shù)字濾波器的例子。 簡(jiǎn)單數(shù)字濾波器 下面例子說(shuō)明了數(shù)字濾波器的基本特征： 1. 單位增益濾波器： 每一個(gè)輸出值yn與輸入值xn 相等： y0= x0 y1

8、=x1 y2 =x2 ...etc 這是一個(gè)經(jīng)常用到的濾波器，濾波器對(duì)輸入信號(hào)沒(méi)有影響。 2. 簡(jiǎn)單的增益濾波器： y n = Kx n 其中K是常數(shù)， 該濾波器只使輸入信號(hào)有一個(gè)K倍的增益。 當(dāng)K > 1時(shí)，濾波器是一個(gè)放大器，當(dāng)0 < K < 1時(shí)，它是一個(gè)衰減器，當(dāng)K < 0時(shí)，對(duì)應(yīng)的是一個(gè)反相器。上例1只是其的一種特殊的情況。 3. 純延遲濾波器： y n = x n-1 在t = nh時(shí)的輸出值只是簡(jiǎn)單的等于t = (n-1)h時(shí)的輸入值，即信號(hào)延遲時(shí)間h： y0 = x-1 y1 = x0 y2 = x1 y3 = x2 ... etc 注意，

9、由于抽樣是在t = 0 開(kāi)始，輸入值x - 1 在t = -h是不確定的。因此一般假設(shè)在t = 0時(shí)（以及t = 0之前），輸出值都設(shè)為0。 4. 差分濾波器： y n = x n - x n-1 在t = nh時(shí)的輸出值等于當(dāng)前輸入值xn與前一個(gè)輸入值xn-1的差值： 即輸出值是最近一次采樣值間隔h輸入的變化。該濾波器對(duì)信號(hào)的影響就是類(lèi)似于模擬電路中的微分電路。 5. 均值濾波器： 該輸出值是當(dāng)前輸入值和前一個(gè)輸入值的平均值（算術(shù)平均）。 這是一個(gè)簡(jiǎn)單的低通濾波器，其通常將高頻中的信號(hào)過(guò)濾掉。（之后，我們將著眼于更有效的低通濾波器。） 6. 三均值濾波器：

10、 該濾波器是當(dāng)前的輸入值和先前兩個(gè)輸入值的均值，類(lèi)似于先前的那個(gè)均值濾波器。 類(lèi)似于之前，x-1和x-2取0。 7. 中心差分濾波器： 該濾波器的濾波效果類(lèi)似于例（4），輸出值等于當(dāng)前輸入值與前兩個(gè)時(shí)間間隔h差值的二分之一。 附件2：外文原文 INTRODUCTION TO DIGITAL FILTERS Analog and digital filters In signal processing, the function of a filter is to remove unwanted parts of the signa

11、l, 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 quite different in their physical makeup and

12、in how they work. An analog filter uses analog electronic circuits made up from components such as resistors, capacitors and opamps to produce the required filtering effect. Such filter circuits are widely used in such applications as noisereduction, video signal enhancement, graphic equalisers in

13、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 directanalogue of the physical quantity (e.g. a sound or vid

14、eo signal or transducer output) involved. A digital filter uses a digital processor to perform numerical calculations on sampled values of the signal. The processor may be a general-purpose computer such as a PC, or a specialised DSP (Digital Signal Processor) chip. The analog input signal must fi

15、rst be sampled and digitised using an ADC (analog to digital converter). The resulting binary numbers, representing successive sampled values of the input signal, are transferred to the processor, which carries out numerical calculations on them. These calculations typically involve multiplying the

16、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

17、 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. Advantages of using digital filters The following list gives some of the main advantages of digital over analog filters. 1. A digital filter is pr

18、ogrammable, i.e. its operation is determined by a program stored in the processors memory. This means the digital filter can easily be changed without affecting the circuitry (hardware). An analog filter can only be changed by redesigning the filter circuit. 2. Digital filters are easily designe

19、d, tested and implemented on a general-purpose computer or workstation. 3. The characteristics of analog filter circuits (particularly those containing active components) are subject to drift and are dependent on temperature. Digital filters do not suffer from these problems, and so are extreme

20、ly stable with respect both to time and temperature. 4. Unlike their analog counterparts, digital filters can handle low frequency signals accurately. As the speed of DSP technology continues to increase, digital filters are being applied to high frequency signals in the RF (radio frequency) dom

21、ain, which in the past was the exclusive preserve of analog technology. 5. Digital filters are very much more versatile in their ability to process signals in a variety of ways; this includes the ability of some types of digital filter to adapt to changes in the characteristics of the signal.

22、6. Fast DSP processors can handle complex combinations of filters in parallel or cascade (series), making the hardware requirements relatively simple and compact in comparison with the equivalent analog circuitry. Operation of digital filters In this section, we will develop the basic theory of

23、 the operation of digital filters. This is essential to an understanding of how digital filters are designed and used. Suppose the "raw" signal which is to be digitally filtered is in the form of a voltage waveform described by the function V = x(t) where t is time. This signal is sampled at ti

24、me intervals h (the sampling interval). The sampled value at time t = ih is x i = x ( ih ) Thus the digital values transferred from the ADC to the processor can be represented by the sequence x0 , x1 , x2 , x3 , ... corresponding to the values of the signal waveform at t = 0, h, 2h, 3h, ...

25、 and t = 0 is the instant at which sampling begins. At time t = nh (where n is some positive integer), the values available to the processor, stored in memory, are x0 , x1 , x2 , x3 , ... x n Note that the sampled values xn+1, xn+2 etc. are not available, as they havent happened yet! y0 , y1 , y

26、2 , y3 , ... y n In general, the value of yn is calculated from the values x0, x1, x2, x3, ... , xn. The way in which the ys are calculated from the xs determines the filtering action of the digital filter. In the next section, we will look at some examples of simple digital filters. Exampl

27、es of simple digital filters The following examples illustrate the essential features of digital filters. 1. Unity gain filter: Each output value yn is exactly the same as the corresponding input value xn: y0= x0 y1 =x1 y2 =x2 ...etc This is a trivial case in wh

28、ich the filter has no effect on the signal. 2. Simple gain filter: y n = Kx n where K = constant. This simply applies a gain factor K to each input value. K > 1 makes the filter an amplifier, while 0 < K < 1 makes it an attenuator. K < 0 corresponds to an inverting amplifier. Example (1) above

29、 is simply the special case where K = 1. 3. Pure delay filter: y n = x n-1 The output value at time t = nh is simply the input at time t = (n-1)h, i.e. the signal is delayed by time h: y0 = x-1 y1 = x0 y2 = x1 y3 = x2 ... etc Note that as sampling is assumed to commence at t = 0, the inp

30、ut value x-1 at t = -h is undefined. It is usual to take this (and any other values of x prior to t = 0) as zero. 4.Two-term difference filter: y n = x n - x n-1 The output value at t = nh is equal to the difference between the current input xn and the previous input xn-1:

31、 i.e. the output is the change in the input over the most recent sampling interval h. The effect of this filter is similar to that of an analog differentiator circuit. 5. Two-term average filter: The output is the average (arithmetic mean) of the current and previous input:

32、 This is a simple type of low pass filter as it tends to smooth out high-frequency variations in a signal. (We will look at more effective low pass filter designs later). 6. Three-term average filter: This is similar to the previous example, with the average being taken of the current and two previous inputs: As before, x-1 and x-2 are taken to be zero. 7. Central difference filter: This is similar in its effect to example (4). The output is equal to half the change in the input signal over the previous two sampling intervals: