摘要
滤波是滤除信号中某些特定频率的波形的技术,在数字信号处理中,主要用于滤除噪声和干扰信号。由于噪声和干扰信号的不确定性,采用固定滤波系数的数字滤波器无法达到最佳的效果。自适应滤波器能够随着环境的改变而改动滤波器自身的参数和结构,从而能够随着噪声和干扰信号的不断变化修正滤波器的参数和结构,最终实现较理想的滤波。本文研究了最小均方差(LMS)算法,并结合自适应滤波器的结构和原理,设计出FIR结构自适应滤波器。最后给出MATLAB仿真结果,并利用DSP验证自适应滤波器的性能。
The filtering is a technology to filter the waveform of some certain frequencies. In digital signal processing, the filtering is mainly used to filter noise and interference signals. Because of the uncertainty of noise and interference signal, using the digital filter of fixed filter coefficients can＇t achieve the best effect. However, the self-adapting filter can change its parameters and structure with the change of the environments which can accommodate to the changing noise and interference signals so as to realize the ideal filter. After studying the Least Mean Square algorithm （here referred as LMS）, as well as analyzing the structure and principle the of the self-adapting filter, the paper designed a self-adapting filter of FIR structure. In the end, it gave the MATLAB simulation results, and used DSP to test the performance of the new design.
出处
《微型机与应用》
2015年第21期16-20,共5页
Microcomputer & Its Applications
基金
福建省高等学校新世纪优秀人才支持计划项目(JA12181)
国家自然科学基金资助项目(51579114)
