DocumentCode :
691069
Title :
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
Link To Document :
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