A Fast Robust Recursive Least-Squares Algorithm

被引：39

作者：

Rey Vega, Leonardo ^{[1
,2
]}

Rey, Hernan ^{[3
]}

Benesty, Jacob ^{[4
]}

Tressens, Sara ^{[2
]}

机构：

[1] Univ Buenos Aires, CONICET, RA-1063 Buenos Aires, DF, Argentina

[2] Univ Buenos Aires, Dept Elect, RA-1063 Buenos Aires, DF, Argentina

[3] Inst Ingn Biomed FIUBA, RA-1063 Buenos Aires, DF, Argentina

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

来源：

IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2009年 / 57卷 / 03期

关键词：

Acoustic echo cancellation; impulsive noise; recursive least-squares algorithm; robust filtering; system identification; FILTERS; THEOREM;

D O I：

10.1109/TSP.2008.2010643

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：

We present a fast robust recursive least-squares (FRRLS) algorithm based on a recently introduced new framework for designing robust adaptive filters. The algorithm is the result of minimizing a cost function subject to a time-dependent constraint on the norm of the filter update. Although the characteristics of the exact solution to this problem are known, there is no closed-form solution in general. However, the approximate solution we propose is very close to the optimal one. We also present some theoretical results regarding the asymptotic behavior of the algorithm. The FRRLS is then tested in different environment's for system identification and acoustic echo cancellation applications.

引用

页码：1209 / 1216

页数：8

共 50 条

[31] On the recursive total least-squares
Pham, C
Ogunfunmi, T
[J]. 1997 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I - V: VOL I: PLENARY, EXPERT SUMMARIES, SPECIAL, AUDIO, UNDERWATER ACOUSTICS, VLSI; VOL II: SPEECH PROCESSING; VOL III: SPEECH PROCESSING, DIGITAL SIGNAL PROCESSING; VOL IV: MULTIDIMENSIONAL SIGNAL PROCESSING, NEURAL NETWORKS - VOL V: STATISTICAL SIGNAL AND ARRAY PROCESSING, APPLICATIONS, 1997, : 1989 - 1992
[32] A fast least-squares algorithm for population inference
R Mitchell Parry
May D Wang
[J]. BMC Bioinformatics, 14
[33] A fast least-squares algorithm for population inference
Parry, R. Mitchell
Wang, May D.
[J]. BMC BIOINFORMATICS, 2013, 14
[34] NUMERICAL DIVERGENCE OF FAST RECURSIVE LEAST-SQUARES TRANSVERSAL FILTERS
BOTTO, JL
[J]. RAIRO-AUTOMATIQUE-PRODUCTIQUE INFORMATIQUE INDUSTRIELLE-AUTOMATIC CONTROL PRODUCTION SYSTEMS, 1988, 22 (03): : 231 - 254
[35] REGULARIZED FAST RECURSIVE LEAST-SQUARES ALGORITHMS FOR ADAPTIVE FILTERING
HOUACINE, A
[J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1991, 39 (04) : 860 - 871
[36] IMPLEMENTATION OF NUMERICALLY ROBUST FAST RECURSIVE LEAST-SQUARES ADAPTIVE FILTERS USING INTERVAL ARITHMETIC
CALLENDER, CP
COWAN, CFN
[J]. ELECTRONICS LETTERS, 1992, 28 (07) : 692 - 693
[37] Robust recursive least squares adaptive beamforming algorithm
Song, X
Wang, J
Wang, H
[J]. IEEE INTERNATIONAL SYMPOSIUM ON COMMUNICATIONS AND INFORMATION TECHNOLOGIES 2004 (ISCIT 2004), PROCEEDINGS, VOLS 1 AND 2: SMART INFO-MEDIA SYSTEMS, 2004, : 238 - 241
[38] A robust recursive least squares passive location algorithm
Wu, Hao
Chen, Shuxin
Hou, Zhiqiang
Zhang, Hengyang
[J]. Journal of Computational Information Systems, 2013, 9 (04): : 1263 - 1270
[39] Robust Recursive Least-Squares Adaptive-Filtering Algorithm for Impulsive-Noise Environments
Bhotto, Md. Zulfiquar Ali
Antoniou, Andreas
[J]. IEEE SIGNAL PROCESSING LETTERS, 2011, 18 (03) : 185 - 188
[40] Linearly-Constrained Recursive Total Least-Squares Algorithm
Arablouei, Reza
Dogancay, Kutluyil
[J]. IEEE SIGNAL PROCESSING LETTERS, 2012, 19 (12) : 821 - 824

← 1 2 3 4 5 →