Novel sign subband adaptive filter algorithms with individual weighting factors

被引:48
作者
Yu, Yi [1 ,2 ]
Zhao, Haiquan [1 ,2 ]
机构
[1] Minist Educ, Key Lab Magnet Suspens Technol & Maglev Vehicle, Chengdu, Peoples R China
[2] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu, Peoples R China
基金
美国国家科学基金会;
关键词
Sign subband adaptive filter; Individual weighting factor; Proportionate sign subband adaptive filter; Impulsive interference; System identification; Acoustic echo cancellation; SQUARE-DEVIATION ANALYSIS; CONVERGENCE;
D O I
10.1016/j.sigpro.2015.11.007
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
This paper presents a new sign subband adaptive filter (SSAF) algorithm with an individual-weighting-factor (IWF) for each subband, instead of a common weighting factor in the original SSAF algorithm, called the IWF-SSAF. Each individual weighting factor only depends on the corresponding subband input signal power. Compared with the SSAF algorithm, the proposed approach fully utilizes the inherent decorrelating property of subband adaptive filter for colored inputs, leading to a better convergence performance. After that, to further enhance the performance of the IWF-SSAF in a sparse system, an improved proportionate IWF-SSAF (IWF-IPSSAF) algorithm is proposed. The proposed algorithms not only inherit the good robustness of sign algorithm against impulsive interferences, but also obtain a significant improvement in the performance as compared to their counterparts (i.e., SSAF and IPSSAF), in terms of the convergence rate and tracking capability. Besides, the IWF-IPSSAF algorithm has faster convergence rate than the IWF-SSAF algorithm for sparse impulse responses. Finally, the performances of two proposed algorithms are demonstrated in the system identification and the acoustic echo cancellation with double-talk. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:14 / 23
页数:10
相关论文
共 28 条
[1]   A family of proportionate normalized subband adaptive filter algorithms [J].
Abadi, Mohammad Shams Esfand ;
Kadkhodazadeh, Sima .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2011, 348 (02) :212-238
[2]  
[Anonymous], 2003, Fundamentals of Adaptive Filtering
[3]  
Benesty J, 2002, INT CONF ACOUST SPEE, P1881
[4]   Proportionate normalized least-mean-squares adaptation in echo cancelers [J].
Duttweiler, DL .
IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING, 2000, 8 (05) :508-518
[5]   Steady-state mean-square deviation analysis of improved normalized subband adaptive filter [J].
Jeong, Jae Jin ;
Koo, Keunhwi ;
Koo, Gyogwon ;
Kim, Sang Woo .
SIGNAL PROCESSING, 2015, 106 :49-54
[6]   Sign subband adaptive filter with l1-norm minimisation-based variable step-size [J].
Kim, J. H. ;
Chang, J. -H. ;
Nam, S. W. .
ELECTRONICS LETTERS, 2013, 49 (21) :1325-1326
[7]  
Lee K.A., 2009, Subband Adaptive Filtering: Theory and Implementation
[8]   Improving convergence of the NLMS algorithm using constrained subband updates [J].
Lee, KA ;
Gan, WS .
IEEE SIGNAL PROCESSING LETTERS, 2004, 11 (09) :736-739
[9]   Inherent decorrelating and least perturbation properties of the normalized subband adaptive filter [J].
Lee, Kong A. ;
Gan, Woon S. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2006, 54 (11) :4475-4480
[10]   A variable step-size sign algorithm for channel estimation [J].
Li, Yuan-Ping ;
Lee, Ta-Sung ;
Wu, Bing-Fei .
SIGNAL PROCESSING, 2014, 102 :304-312