An optimized NLMS algorithm for system identification

被引：71

作者：

Ciochina, Silviu ^{[1
]}

Paleologu, Constantin ^{[1
]}

Benesty, Jacob ^{[2
]}

机构：

[1] Univ Politehn Bucuresti, Bucharest 061071, Romania

[2] Univ Quebec, INRS EMT, Montreal, PQ H5A 1K6, Canada

来源：

SIGNAL PROCESSING | 2016年 / 118卷

关键词：

Echo cancellation; Normalized least-mean-square (NLMS) algorithm; Variable step-size NLMS; Variable regularized NLMS; Adaptive filters; STEP-SIZE NLMS; AFFINE PROJECTION ALGORITHM; ACOUSTIC ECHO CANCELLATION; KALMAN FILTER; REGULARIZATION; ORDER;

D O I：

10.1016/j.sigpro.2015.06.016

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The normalized least-mean-square (NLMS) adaptive filter is widely used in system identification. In this paper, we develop an optimized NLMS algorithm, in the context of a state variable model. The proposed algorithm follows a joint-optimization problem on both the normalized step-size and regularization parameters, in order to minimize the system misalignment. Consequently, it achieves a proper compromise between the performance criteria, i.e., fast convergence/tracking and low misadjustment. Simulations performed in the context of acoustic echo cancellation indicate the good features of the proposed algorithm. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：115 / 121

页数：7

共 28 条

[1]

Benesty J., 2003, Adaptive Signal Processing: Applications to Real-World Problems

[2] A nonparametric VSSNLMS algorithm [J].