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应用科学学报 ›› 2004, Vol. 22 ›› Issue (3): 370-374.

• 论文 • 上一篇    下一篇

基于峰态的盲信号分离

叶骏1, 刘峰2, 徐柏龄1   

  1. 1 南京大学声学所近代声学国家重点实验室 江苏南京 210093;
    2 南京邮电学院信息工程系 江苏南京 210003
  • 收稿日期:2003-04-30 修回日期:2003-11-03 出版日期:2004-09-30 发布日期:2004-09-30
  • 作者简介:叶骏(1979-),男,贵州贵阳人,学士;徐柏龄(1941-),男,江苏南通人,教授,博导.
  • 基金资助:
    江苏省重点实验室资助项目(K02090)

Blind Signal Separation by Kurtosis

YE Jun1, LIU Feng2, XU Bo-ling1   

  1. 1. State Key Laboratory of Modern Acoustics, Institute of Acoustics, Nanjing University, Nanjing 210093, China;
    2. Department of Information Engineering, Nanjing University of Post and Telecommunications, Nanjing 210003, China
  • Received:2003-04-30 Revised:2003-11-03 Online:2004-09-30 Published:2004-09-30

PDF

63

被引次数

5

摘要： 就一种基于信号峰态(kurtosis)极值化的盲信号分离方法进行了探讨.首先介绍算法理论,然后提出了一种简化快速的最速下降算法,解决了收敛指向性的问题,并将对混合语音信号的分离扩展到混合图像信号的分离.实验结果表明,同其他基于峰态的盲分离算法相比,其分离效果好,而且在收敛速度、运算复杂度方面有显著的优势.

关键词: 最速下降法, 峰态, 盲信号分离

Abstract: Blind source separation is an interesting project in the field of signal processing and has a wide development and application prospect. Independent component analysis is one of important methods of blind signal separation, so a kurtosis maximization/minimization-based blind signal separation method is considered in this paper, and the mixture of signals is limited to be instant(non-convolutive). Firstly, the basic theory of separation is introduced, and then the detail of our algorithm is presented. The method is applied to the separation of mixed speech signals and mixed image signals. The results of experiments prove that the advantage of this algorithm is good performance of separation and fast convergence through simple computation.

Key words: blind signal separation, kurtosis, steepest-descent algorithm

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