基于dsp数字信号处理器数字滤波器设计的英文翻译及原文

基于dsp数字信号处理器数字滤波器设计的英文翻译及原文内容摘要：

are wellestablished 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 (. a sound or video 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 generalpurpose puter such as a PC, or a specialized DSP (Digital Signal Processor) chip. The analog input signal must first be sampled and digitized 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 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 optimal control and adaptive control and selflearning control were related to many parameters, multivariate plex control system, all belong to the modern control theory of research. Adaptive DF has the very strong selflearning, since the tracking function. It on the radar and sonar beam forming, slowly noise suppression, noise signal processing, the munication channel adaptive equilibrium, the echo of the long distance telephone offset, etc have gained wide application, and promote the development of modern control theory. Adaptive filter is the one of the modern filter. It is an important application of adaptive signal processing that was developed in the 1940s. Adaptive filter has been used widely in system identification, noise canceller, adaptive line enhance, adaptive equalization of munication channel, linear predication, adaptive array antenna and so on. Adaptive filter is opposite to fixed coefficients filter. During digital signal processing, a number of unpredictable signals, noises or timevarying signals often need to process, it is impossible to achieve optimal filtering for fixed coefficient filter, so adaptive filter must be designed to track the change of signal and noise. The unique structure and instruction of TMS320VC5402 DSP provide the convenient condition for designing adaptive filter. 2 Principle of Adaptive Filter Adaptive filter which belongs to the category of modern filter, the adaptive filter is a relatively fixed filters, a fixed filter belongs to the classical filter, the filter39。 s frequency is fixed, the adaptive filter frequency is automatically adapt to changes in the input signal, so its applicable range. In the absence of any a priori knowledge about the signal and noise conditions, the adaptive filter using a moment before the time of filter parameters automatically adjust the filter parameters have been obtained, statistical characteristics of signal and noise to adapt to unknown or random change, so as to achieve the optimal filtering. The adaptive filter, the filter parameters is an results, automatically adjusting filter parameters is now time to adapt, statistical characteristics of signal and noise unknown or timevarying, so as to achieve the optimal filtering. The adaptive filter is essentially a can adjust its transmission characteristics in order to achieve optimal Wiener filter. Adaptive filter consists of two basic parts: the filter which applies the required processing on the ining signal which is to be filtered, and an adaptive algorithm, which adjusts the coefficients of that filter to somehow improve its performance. When adaptive filter is designed, the autocorrelation function of signals and noises can not be known in advance. During the filtering, with the autocorrelation function of signals and noises changing slowly over time, filter can automatically adapt and adjust to meet the requirements of the minimum mean squared error. Fig 1 Structure of Adaptive Filter Fig 1 shows the structure of adaptive filter. The objective is to filter the input signal, X(n), with an adaptive filter in such a manner that it matches the desired signal, d(n). The desired signal, d(n), is subtracted from the filtered signal, Y(n), to generate an error signal, e(n). 3 Structure of Filter and LMS Algorithm Structure of Adaptive FIR Filter Several types of filter structures can be implemented in the design of the adaptive filters such as Infinite Impulse Response (IIR) or Finite Impulse Response (FIR). Based on time domain characteristics of digital filter impulse response function, the digital filter can be divided into two kinds, namely infinite impulse corresponding IIR filter and finite impulse response FIR digital filter has the advantage that can make use of the results of analog filter design, and the design of the analog filter can check a large number of graphs, convenient and simple. Its disadvantage is that the nonlinear phase。 If need to linear phase, the allpass work is adopted to improve the phase correction. Image processing and data acquisition transmission require filter with linear phase characteristic. And can realize linear phase FIR digital filter, and can be arbitrary amplitude characteristics. FIR filters Can get a strict linear phase, but due to system function that the FIR filter poles are fixed at the origin, so can only use higher order to achieve its high selectivity, for the same filter design index, FIR filter required by the order number is 5 to 10 times greater than the IIR, so the cost is higher, signal delay is bigger also. But if required the same。