CONVERGENCE EVALUATION OF A RANDOM STEP-SIZE NLMS ADAPTIVE ALGORITHM IN SYSTEM IDENTIFICATION

摘要：

A new and simple method to adjust the step-size (μ) of the standard Normalized Least Mean Square (NLMS) adaptive algorithm is proposed here. The value of μ is totally controlled by the use of a Pseudorandom Noise (PRN) uniform distribution that is defined by values from 0 to 1. Randomizing the step-size parameter eliminates much of the trade-off between residual error and convergence speed compared with the fixed step-size. The mean-square error (MSE) of using the new algorithm in the adaptation process of system identification over a defined communication channel is investigated here. The proposed uniformly distributed step-size variation in the adaptation process of the NLMS algorithm makes it possible to have similar convergence rate but lower steady state error compared with fixed μ.

关键词： Adaptive algorithms NLMS System Identification

作者: S.A.Jimaa T.Shimamura

作者单位: Khalifa University of Science, Technology and Research Communications Engineering Department.Sharjah Saitama University Department of Information and Computer Sciences 255 Shimo-Okubo,Sakura-ku, Saitam

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 135-138

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）