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

• 学术论文 • 上一篇    下一篇

分布式子带自适应滤波算法

倪锦根, 马兰申   

  1. 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 发布日期: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   

  1. 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

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

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