Convergence performances of various adaptive filter algorithms with application to system identification

S. Jimaa, Saeed Al-Ali
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引用次数: 3

Abstract

This paper examines the performance of mean square error (MSE) using various adaptive filtering algorithms in the adaptation process of system identification over two defined communication channels. The MSE performances of the proposed algorithms are compared with that of the standard Normalized Least Mean Square (NLMS) algorithm. To enhance the adaptation performance, non-mean-square algorithms have been utilized, for instant, Least Mean Fourth (LMF) algorithm. Also, switching algorithm led to better performance. In this paper, random step size NLMS, switching between NLMS and LMF, and LMS+F mixed norm algorithms have been implemented and their performances over two defined Finite Impulse Response (FIR) channels were tested in comparison with the standard NLMS.
各种自适应滤波算法的收敛性能及其在系统辨识中的应用
本文研究了在两个已定义的通信信道上使用各种自适应滤波算法进行系统识别的自适应过程中均方误差(MSE)的性能。将所提算法的MSE性能与标准的归一化最小均方(NLMS)算法进行了比较。为了提高自适应性能,采用了非均方算法,即最小平均四次(LMF)算法。同时,切换算法也带来了更好的性能。本文实现了随机步长NLMS、NLMS和LMF之间的切换以及LMS+F混合范数算法,并与标准NLMS相比,在两个定义的有限脉冲响应(FIR)通道上测试了它们的性能。
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