独立分量分析及其在信号处理中的应用被引量：22

Independent Component Analysis and Its Application to Signal Processing

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摘要独立分量分析是近年来由盲源分离技术发展而来的一种多维信号统计处理方法,可以根据源信号的基本统计特征,由观测数据最终恢复出源信号.该方法在很多与信号处理相关的领域有强大的应用潜力.文中简要介绍了独立分量分析的基本概念、原理及各种独立性判据,综述了独立分量分析在语音信号处理、图像处理、移动通信等领域的应用,最后结合笔者的研究探索,总结了独立分量分析的研究进展和发展趋势. As a new statistical processing technique for multidimensional signals recently developing from blind source separation,independent component analysis（ICA） can recover latent independent sources from measured mixed data according to the basic statistical features of the sources,so that it has been successfully applied to many signal processing-related fields.In this paper,after briefly introducing the basic concept,principle and indepen-dent criteria of ICA,the authors put their emphases on the practical applications of ICA to such fields as speech signal processing,image processing and wireless communication,and then,based on their research results,they sum up the research progress and development direction of ICA.

作者杨俊美余华韦岗

机构地区华南理工大学电子与信息学院

出处《华南理工大学学报（自然科学版）》 EI CAS CSCD 北大核心 2012年第11期1-12,共12页 Journal of South China University of Technology(Natural Science Edition)

基金国家自然科学基金资助项目(61004054 61071212) 华南理工大学中央高校基本科研业务费专项资金资助项目(2012ZZ0028)

关键词信号处理独立分量分析盲源分离高阶统计量 signal processing independent component analysis blind source separation higher-order statistics

分类号 TN911 [电子电信—通信与信息系统]

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