• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2011, Vol. 33 ›› Issue (10): 159-163.

• 论文 • 上一篇    下一篇

一种基于动态源数目估计的RLS盲分离算法

汤〓辉,王〓殊   

  1. (华中科技大学电信系,湖北 武汉 430074)
  • 收稿日期:2010-12-01 修回日期:2011-02-23 出版日期:2011-10-25 发布日期:2011-10-25

A RLS BSS Algorithm Based on Dynamic Source Number Estimation

TANG Hui,WANG Shu   

  1. (Department of Eletronics and Information,Huazhong University of Science and Technology,Wuhan 430074,China)
  • Received:2010-12-01 Revised:2011-02-23 Online:2011-10-25 Published:2011-10-25

摘要:

针对原始RLS类算法无法用于超定和源信号数目动态变化的盲分离问题,本文采用一种新的在线估计源信号数目的方法。通过在线估计观测信号均值和协方差矩阵,定义一个关于源信号数目的代价函数,然后最小化代价函数可得到源信号数目的估计。并且利用估计得到的源数目动态调整RLS算法中的分离矩阵及其它相关参数矩阵的维数,进而使得改进RLS盲分离算法能够有效地分离超定和数目动态变化的源信号。仿真结果表明,新的算法比现有算法具有更好的收敛性和分离性能。

关键词: RLS算法, 动态源数目估计, 超定盲分离, 自适应维数调整

Abstract:

Since the RLSlike algorithm can not be used in the supercondition and dynamic source numbers’ blind source separation problem, we introduce a novel RLS algorithm combing with an online source number estimation method. First it defines a cost function related to the source number based on estimation of the  mean value and the covariance matrix of the observed signals, then minimizes the function to achieve the estimation of the source number. The dimensions of the separated matrix and other related parameter matrixes can be dynamically modified according to the estimated source number, which makes the RLSlike algorithm able to  separate the source signals efficiently in the supercondition and dynamic source numbers environments. Computer simulations show that the new algorithms is better than the existing algorithm with faster convergence and better separation results.

Key words: RLS algorithm;dynamic estimation of source number;supercondition blind source separation;adaptive dimension adjust