毕业设计（论文）-LMS自适应滤波器的DSP实现.doc

文档介绍：LMS自适应滤波器的DSP实现
LMS自适应滤波器的DSP实现
摘要
在传统的LMS(Least Mean Square)算法中,固定步长的选取影响收敛速度与稳态误差,而且两者不可兼得。因此,为在相应的领域内合理使用此类算法,针对这个问题在对多种自适应滤波LMS类算法进行原理分析后,得出此类算法在不同领域的特点,对今后不同人群的合理使用提供了良好条件。
为了达到最佳的滤波效果,使自适应滤波器在工作环境变化时自动调节其单位脉冲响应特性,提出了一种自适应算法:最小均方算法(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,所以获得了极为广泛的应用。针对用硬件实现LMS算法的自适应滤波器存在的诸多缺点,采用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,应用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,还能用于系统识别。
关键词:自适应滤波;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 绪论 1
研究目的和意义 1
研究背景及现状 1
本文研究内容 2
2 自适应滤波LMS 类算法种类 3
传统LMS算法 3
变步长的LMS算法 3
变化域的LMS算法 4
DSP 5
MATLAB 6
本章小结 6
3 自适应滤波器的DSP实现 7
DSP实现 7
流程图 7
设计思想 8
程序实现结果 9
本章小结 11
4 自适应滤波器的算法实现 12
自适应滤波器的MATLAB仿真 12
C语言的实现 13
汇编的实现 14