Design and Implementation of FIR Bandpass Filter Based on Matlab
Abstract: Based on Matlab's FDATOOL filter design and analysis software, a FIR digital bandpass filter is designed and a noisy speech signal is filtered. The filter is implemented on the DSP using assembly language programming. The experimental results show that the digital bandpass filter is accurate, stable, easy to transplant, and has strong practicability and flexibility.
Key words: FIR digital bandpass filter; speech denoising; DSP; Matlab
introduction
With the rapid development of electronic technology, people are gradually entering the digital age. Digital filters are getting more and more people's attention, and they are widely used in modern telecommunication equipment and various control systems, such as voice processing, image processing, and communication. , television, radar, biomedical signal processing, etc. The digital filter can be divided into an infinite-length unit impulse response (IIR) filter and a finite-length unit impulse response (FIR) filter according to the time domain characteristics of its impulse response function. Although the IIR filter can take advantage of the results of the analog filter design, the design of the analog filter has a large number of charts to check, which is convenient and simple, but its phase is nonlinear. Both image processing and data transmission require that the channel have a linear phase while having arbitrary amplitude characteristics. Furthermore, the unit impulse response of the FIR filter is finitely long and the filter must be stable. With the continuous improvement of Matlab software and signal processing toolbox, the Matl ab signal processing toolbox can be used to quickly and efficiently implement digital filter design, analysis and simulation. In this paper, a FIR digital bandpass filter is designed firstly by Matlab, and a noisy speech signal is filtered. Then the filter is implemented on the TMS320C5402 chip produced by TI.
1 FIR digital bandpass filter design principle
Let the FIR filter unit impulse response h(n) be N, and its system function H(z) is:
The FIR filter is designed to select a finite length of h(n) so that the transfer function meets the technical requirements. Generally, the desired ideal filter frequency response is given first. 
, export hd(n). Since the impulse response hd(n) of an ideal filter is an infinitely long non-causal sequence, and the design is that hd(n) is a finite-length FIR filter, the finite-length sequence hd(n) is used to approximate infinity. Long sequence h(n). Assume:
It can be seen that the window function not only affects the waveform of the original signal in the time domain, but also affects the waveform in the frequency domain.
2 Using Matlab to aid design and simulation
To design an FIR filter, the key is to get the correct h(n) coefficient. There are two ways to load the generated filter coefficients into the target DSP program:
(1) input the filter coefficient to a C language header file, and add the header file to the built project;
(2) directly load the generated filter coefficients into a variable of the DSP program.
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