分布式子带自适应滤波算法

doi:10.3969/j.issn.0372-2112.2015.11.013

电子学报 ›› 2015, Vol. 43 ›› Issue (11): 2225-2231.DOI: 10.3969/j.issn.0372-2112.2015.11.013

分布式子带自适应滤波算法

倪锦根, 马兰申

苏州大学电子信息学院, 江苏苏州 215006

收稿日期:2014-04-23 修回日期:2014-07-07 出版日期:2015-11-25
- 作者简介:
- 倪锦根 男,1979年11月生,江苏省兴化市人.毕业于复旦大学,获理学博士学位,现为苏州大学电子信息学院副教授、硕士生导师,IEEE会员.主要研究方向为自适应滤波、分布式估计、滤波器组设计等.E-mail:jni@suda.edu.cn;马兰申 男,1988年4月生,安徽省亳州市人.现为苏州大学硕士研究生.研究方向为自适应滤波和分布式估计.E-mail:malanlong@163.com
- 基金资助:
- 国家自然科学基金 (No.61101217); 江苏省自然科学基金 (No.BK20131164)

Distributed Subband Adaptive Filtering Algorithms

NI Jin-gen, MA Lan-shen

School of Electronic and Information Engineering, Soochow University, Suzhou, Jiangsu 215006, China

Received:2014-04-23 Revised:2014-07-07 Online:2015-11-25 Published:2015-11-25
- Supported by:
- National Natural Science Foundation of China (No.61101217); Natural Science Foundation of Jiangsu Province, China (No.BK20131164)

摘要/Abstract

摘要：

为了解决分布式最小均方算法在输入信号相关性较高时收敛速度较慢、分布式仿射投影算法计算复杂度较高等问题,本文提出了两种分布式子带自适应滤波算法,即递增式和扩散式子带自适应滤波算法.分布式子带自适应滤波算法将节点信号进行子带分割来降低信号的相关性,从而加快收敛速度.由于用于子带分割的滤波器组中包含了抽取单元,所以分布式子带自适应滤波算法和对应的分布式最小均方算法的计算复杂度相近.仿真结果表明,与分布式最小均方算法相比,分布式子带自适应滤波算法具有更好的收敛性能.

关键词: 自适应信号处理, 自适应网络, 子带自适应滤波

Abstract:

To address the problem of slow convergence rate of the distributed least mean square algorithms for highly correlated input signals and the problem of high computational complexity of the distributed affine projection algorithms,this paper proposes two distributed subband adaptive filtering algorithms,i.e.,the incremental and diffusion subband adaptive filtering algorithms.The distributed subband adaptive filtering algorithms partition the signals of nodes to reduce their correlation so that their convergence rate can be increased.The computational complexities of the distributed subband adaptive filtering algorithms are close to those of their corresponding distributed least mean square algorithms due to decimation operations included in the filter banks used for subband partition.Simulation results show that the distributed subband adaptive filtering algorithms exhibit good performance as compared to the corresponding distributed least mean square algorithms.

Key words: adaptive signal processing, adaptive networks, subband adaptive filtering

中图分类号:

TN911.72

倪锦根, 马兰申. 分布式子带自适应滤波算法[J]. 电子学报, 2015, 43(11): 2225-2231.

NI Jin-gen, MA Lan-shen . Distributed Subband Adaptive Filtering Algorithms[J]. Acta Electronica Sinica, 2015, 43(11): 2225-2231.

参考文献

[1] Sayed A H,Tu S Y,et al.Diffusion strategies for adaptation and learning over networks[J]. IEEE Signal Processing Magazine,2013,30(3):155-171.
[2] Lopes C G,Sayed A H.Incremental adaptive strategies over distributed networks[J]. IEEE Transactions on Signal Processing,2007,55(8):4064-4077.
[3] Lopes C G,Sayed A H.Diffusion least-mean squares over adaptive networks:formulation and performance analysis[J]. IEEE Transactions on Signal Processing,2008,56(7):3122-3136.
[4] Cattivelli F S,Sayed A H.Diffusion LMS strategies for distributed estimation[J]. IEEE Transactions on Signal Processing,2010,58(3):1035-1048.
[5] Liu Y,Li C,Zhang Z.Diffusion sparse least-mean squares over networks[J]. IEEE Transactions on Signal Processing,2012,60(8):4480-4485.
[6] Li C,Shen P,Liu Y.Diffusion information theoretic learning for distributed estimation over network[J]. IEEE Transactions on Signal Processing,2013,61(16):4011-4024.
[7] Li L,Chambers J A,et al.Distributed estimation over an adaptive incremental network based on the affine projection algorithm[J]. IEEE Transactions on Signal Processing,2010,58(1):151-164.
[8] 李雷雷,何剑辉,张勇刚.分布式网络中的仿射投影自适应算法[J]. 中国传媒大学学报(自然科学版),2012,19(2):34-43. LI Lei-lei,HE Jian-hui,ZHANG Yong-gang.Affine projection algorithms over distributed wireless networks[J]. Journal of Communication University of China(Science and Technology),2012,19(2):34-43.(in Chinese)
[9] Sayed A H.Adaptive Filters[M]. Hoboken,New Jersey:John Wiley & Sons,2008.
[10] Lee K A,Gan W S.Improving convergence of the NLMS algorithm using constrained subband updates[J]. IEEE Signal Processing Letters,2004,11(9):736-739.
[11] Lee K A,Gan W S,kuo S M.Subband Adaptive Filtering Theory and Implementation[M]. Hoboken,New Jersey:John Wiley & Sons,2009.
[12] 倪锦根,商慧亮,李锋.归一化子带自适应滤波器步长控制[J]. 电子与信息学报,2009,31(11):2606-2609. NI Jin-gen,LI Feng,SHANG Hui-liang.Step-size control for the normalized subband adaptive filter[J]. Journal of Electronics & Information Technology,2009,31(11):2606-2609.(in Chinese)
[13] Ni J,Li F.A variable step-size matrix normalized subband adaptive filter[J]. IEEE Trans on Audio,Speech,and Language Processing,2010,18(6):1290-1299.
[14] Yang F,Wu M,et al.An improved multiband-structured subband adaptive filter algorithm[J]. IEEE Signal Processing Letters,2012,19(10):647-650.
[15] Ni J,Chen X,Yang J.Two variants of the sign subband adaptive filter with improved convergence rate[J]. Signal Processing,2014,96(B):325-331.
[16] Tu S Y,Sayed A H.Mobile adaptive networks[J]. IEEE Journal of Selected Topics in Signal Processing,2011,5(4):649-664.
[17] Quan Z,Zhang W,et al.Optimal spectral feature detection for spectrum sensing at very low SNR[J]. IEEE Transactions on Communications,2011,59(1):201-212.
[18] Shin Y J,Sayed A H,Shen X.Adaptive models for gene networks[J]. PLoS ONE,2012,7(2):e31657.
[19] Lorenzo P Di,Barbarossa S,Sayed A H.Distributed spectrum estimation for small cell networks based on sparse diffusion adaptation[J]. IEEE Signal Processing Letters,2013,20(12):1261-1265.
[20] Lorenzo P Di,Barbarossa S,Sayed A H.Bio-inspired decentralized radio access based on swarming mechanisms overadaptive networks[J]. IEEE Transactions on Signal Processing,2013,61(12):3183-3197.

分布式子带自适应滤波算法

Distributed Subband Adaptive Filtering Algorithms

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

编辑推荐

Metrics

[1]	吉利鹏, 倪锦根. 偏差补偿符号子带自适应滤波器[J]. 电子学报, 2020, 48(11): 2220-2225.
[2]	闫震海, 杨飞然, 杨军. 一种变正则化矩阵的改进多带结构子带自适应滤波算法[J]. 电子学报, 2017, 45(8): 2019-2025.
[3]	倪锦根, 马兰申. 抗脉冲干扰的分布式仿射投影符号算法[J]. 电子学报, 2016, 44(7): 1555-1560.
[4]	魏进武, 王永良, 陈建文. 双基地机载预警雷达空时自适应处理方法[J]. 电子学报, 2001, 29(S1): 1936-1939.
[5]	李春升;陈杰;周荫清. 机载多通道天线SAR自适应杂波抑制[J]. 电子学报, 2000, 28(3): 93-94.