南京大学学报：自然科学版2011，Vol.47Issue(5)：566-570,5.
基于稀疏特性的欠定盲信号分离算法
Underdetermined blind source separation algorithm based on sparse representation
摘要
Abstract
Based on the insufficient sparsity assumption of the source signals,a new algorithm is presented for underdetermined blind source separation.Different with existing sparse component analysis algorithms which assume that source signals are strictly sparse,the proposed algorithm is able to solve sparse component analysis problem in non-strictly condition;meanwhile,the proposed algorithm is also able to detect the clustering spaces number when the sources number is unknown previously.The fuzzy clustering method is also helpful in the second stage.Simulations are given to demonstrate the effectiveness of the proposed algorithm.关键词
欠定盲分离/模糊聚类/稀疏分量分析Key words
underdetermined blind source separation/fuzzy clustering/sparse component analysis分类
信息技术与安全科学引用本文复制引用
张苏弦,刘海林..基于稀疏特性的欠定盲信号分离算法[J].南京大学学报：自然科学版,2011,47(5):566-570,5.基金项目
国家自然科学基金 （）
广东省自然科学基金 （）
