基于自适应均衡器的LMS和RLS算法仿真分析

摘要

Basic principles of LMS and RLS algorithms based on adaptive equalizer are introduced firstly.Oblivion gene μ is the main factor affecting the convergence performance.The result of the simulation shows that the convergence speed of RLS algorithm is more faster obviously than LMS algorithm, and the errors are smaller than LMS algorithm too.%介绍了自适应均衡器下的LMS和RLS算法的基本原理,并分析了2种算法中的忘却因子μ对LMS和RLS算法收敛性能的影响.通过仿真可知,在相同忘却因子下,RLS算法的收敛速度明显快于LMS算法,并且误差也比LMS算法小.