A Special FCL Clustering and Its Application to Sparse Blind Source Separation

被引：1

作者：

Tong, Yu ^{[1
]}

Zhang, Yunjie ^{[1
]}

机构：

[1] Dalian Maritime Univ, Dept Math, Dalian 116026, Peoples R China

来源：

CEIS 2011 | 2011年 / 15卷

关键词：

FCL; blind source separation; underdetermined sparse signal; REPRESENTATION; SUBSTRUCTURE;

D O I：

10.1016/j.proeng.2011.08.436

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Fuzzy c-Lines (FCL) algorithm is a linear fuzzy clustering algorithm and is constructed to treat linear dates and capture linear substructures. This paper considers a special FCL clustering algorithm, then based on the special FCL clustering algorithm and generalized inverse of vectors, proposes a new two-step clustering algorithms in order to solve the underdetermined sparse blind signal separation. The proposed algorithm provides a new approach for mixing matrix estimation and source signals separation, and simulation results support the validity of the algorithm. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]

引用

页数：5

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