摘要
为了解决传统自适应滤波最小均方(Least Mean Square,LMS)算法中收敛速度与稳态误差之间的矛盾,提出了一种改进算法。该算法在已有变步长LMS算法基础上,引入遗忘因子来影响步长的更新。仿真表明,改进后的算法比原算法不但具有更快的收敛速度,而且具有更小且稳定的稳态误差。
In order to settle the conflict between convergence speed and steady-state mean-error of traditional LMS(Least Mean Square) equalization filtering algorithm,an improvement to the existing variable step LMS algorithm is proposed by introducing the forgetting factor,with which the update of step length can be controlled.Simulation results show that the improved algorithm is faster convergence and smaller mean-error compared with the original one.
出处
《西安邮电学院学报》
2011年第3期6-8,共3页
Journal of Xi'an Institute of Posts and Telecommunications
基金
陕西省教育厅科研基金资助项目(2010JK835)
西安邮电学院中青年科研基金资助项目(ZL2009-22)
关键词
LMS滤波算法
收敛速度
稳态误差
遗忘因子
LMS filtering algorithm
convergence speed
steady-state mean-error
forgetting factor