摘要
最小均方算法的收敛速度和稳态误差之间存在矛盾,为此人们提出了各种变步长LMS算法,其中E-LMS算法是将步长与瞬时误差平方相关联,R-LMS算法是将步长与误差的相关函数相关联。E-LMS算法的抗噪性能较差,在低信噪比条件下性能明显变差,R-LMS算法对突变系统的跟踪能力较差。为此文中给出了一种改进的,基于误差相关函数的VSS-LMS算法,该方法利用E-LMS算法的控制步长策略提高算法的跟踪能力。计算机仿真结果显示,该算法能够同时满足抗噪和跟踪两种要求。
In order to solve the contradictory effect between convergence speed and excess mean square error of the Least Mean Square （LMS） algorithm, some variable step size （VSS） LMS algorithms are proposed. Among these algorithms, the E-LMS algorithm associates the step size with mean square error while the R-LMS algorithm as- sociates the step size with error correlation function. The E-LMS algorithm has poor performance under low signal noise ratio （SNR） condition, and R-LMS algorithm has poor tracking performance for burst systems. In this paper, a modified algorithm based on error correlation function is proposed, whose tracking performance is enhanced by the mean square error. The computer simulation results show that the algorithm has good performance of anti-noise and tracking.
出处
《电子科技》
2013年第7期14-16,20,共4页
Electronic Science and Technology
关键词
最小均方算法
变步长
误差相关函数
均方误差
least mean square
variable step size
error correlation function
mean square error
