Application Studies on Voice Signal Blind Separation of Independent Component Analysis

Author

Peng Zhang ; Wen-juan Li ; Ceng Li ; Guo-hua Wang ; Hui-xian Chen ; Qi-ying Wang

Author_Institution

Inst. of xinxing Appl. Technol., Hefei, China

fYear

2013

fDate

21-23 Sept. 2013

Firstpage

536

Lastpage

539

Abstract

The Independent Component Analysis (ICA) method has applied in the field of blind source separation. On the basis of analyzing ICA, the study ameliorates the FastICA. The conventional FastICA has only a second order convergence rate and combination of static model and batch optimization algorithm. An improved ICA algorithm is therefore proposed to reduce the iteration steps and dynamic the algorithm. The experimental results show that the improved algorithm achieved satisfactory results.

Keywords

blind source separation; convergence; independent component analysis; iterative methods; optimisation; speech processing; FastICA; ICA method; batch optimization algorithm; blind source separation; independent component analysis; iteration step reduction; second order convergence rate; static model; voice signal blind separation; Algorithm design and analysis; Blind source separation; Heuristic algorithms; Independent component analysis; Jacobian matrices; Random variables; Signal processing algorithms; FastICA; blind source analysis; independent component analysis; voice signal;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2013 Third International Conference on

Conference_Location

Shenyang

Type

conf

DOI

10.1109/IMCCC.2013.121

Filename

6840511