數(shù)字濾波器簡(jiǎn)介外文翻譯-資料下載頁(yè)
2025-05-12 01:46本頁(yè)面
【導(dǎo)讀】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)。他們的物質(zhì)組成和工作。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。個(gè)已經(jīng)提出要求的模擬濾波器電路的設(shè)計(jì)。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。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。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。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)。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；在本節(jié)中，我們將介紹數(shù)字濾波器運(yùn)行的基本理論。
【正文】 ital 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 which 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 is simply the special case where K = 1. 3. Pure delay filter: y n = x n1 The output value at time t = nh is simply the input at time t = (n1)h, . the signal is delayed by time h: y0 = x1 y1 = x0 y2 = x1 y3 = x2 ... etc Note that as sampling is assumed to mence at t = 0, the input value x1 at t = h is undefined. It is usual to take this (and any other values of x prior to t = 0) as zero. difference filter: y n = x n x n1 The output value at t = nh is equal to the difference between the current input xn and the previous input xn1: . 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. Twoterm average filter: The output is the average (arithmetic mean) of the current and previous input: This is a simple type of low pass filter as it tends to smooth out highfrequency variations in a signal. (We will look at more effective low pass filter designs later). 6. Threeterm average filter: This is similar to the previous example, with the average being taken of the current and two previous inputs: As before, x1 and x2 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:
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