LMS自适应滤波器的DSP实现.doc

LMS自适应滤波器的DSP实现 LMS自适应滤波器的DSP实现 摘 要LMS(Least Mean Square)算法中，，，，LMS类算法进行原理分析后，， 为了达到最佳的滤波效果，，(LMS算法) 。这种算法实现简单且对信号统计特性变化具有稳健性，LMS算法的自适应滤波器存在的诸多缺点，Matlab工具对基于LMS算法的自适应滤波器进行了仿真试验。仿真结果表明，LMS算法的自适应滤波器不仅可以实现对信号噪声的自适应滤除， 关键词：LMS算法；Matlab；FIR  LMS adaptive filter of the DSP to achieve Abstract The convergent speed and steady state error are affected by the fixed step size and can not be improved simultaneously in classical LMS algorithm. Therefore, to use it correctly in relevant fields, for this contradiction, after analyzing a variety of LMS adaptive filtering algorithms on principle, the characteristic of these algorithms in different fields is presented, this also provides different people`s correct use with a better foundation. In order to achieve the optimum filtering effect, it makes the adaptive filter adjust its units impulse response characteristics automatically on the working environment changed. This paper present s a kind of adaptive algorithm: Least Mean Square (LMS algorithm).As the algorithm is realized simply and has stability with respect to the change of signal statistical characteristics, LMS algorithm is used widely. According to disadvantages of adaptive filter to realize LMS using hardware adaptive filter is simulated which is based on LMS algorithm with Matlab. Result s of simulation show that this kind of adaptive filter not only can filter the signal noise, but also recognize the system. Keywords：adaptive filtering；LMS algorithm；Matlab；FIR. 目 录 1 1 1.1 研究目的和意义 1 1.2 研究背景及现状 1 1.3 本文研究内容 2 2 自适应滤波LMS 类算法种类 3 2.1 传统LMS算法 3 2.2 变步长的LMS算法 3 2.3 变化域的LMS算法 4 2.4 DSP 5 2.5 MATLAB 6 2.6 本章小结 6 3 自适应滤波器的DSP实现 7 3.1 DSP实现 7 3.1.1 流程图 7 3.1.2 设计思想 8 3.2 程序实现结果 9 3.3 本章小结 11 4 自适应滤波器的算法实现 12 4.1 自适应滤波器的MATLAB仿真 12 4.2 C语言的实现 13 4.3 汇编的实现 14 4.4 LMS应用实例 19 4.4 本章小结 20 5 总结和展望 22 5.1 总结 22 5.2 工作展望 22 参 考 文 献 23 1 绪 论 1960 年Widrow 和Hoff 提出最小均方误差 (LMS) 算法。LMS 算法具有计算量小，，，，，。 自适应滤波器属于现代滤波器的范畴，20 世纪40 年代发展起来的自适应信号处理领域的一个重要应用，，，，，，，，， 1.2 研究背景及现状 F