Blind source separation by combining indepandent component analysis with complex discrete wavelet transform

被引：0

作者：

Zhang, Zhong ^{[1
]}

Enomoto, Takeshi ^{[2
]}

Miyake, Tetsuo ^{[1
]}

Imamura, Takashi ^{[1
]}

机构：

[1] Toyohashi Univ Technol, Dept Prod Syst Engn, Toyohashi, Aichi, Japan

[2] JTEKT Corp, Osaka, Japan

来源：

2007 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION, VOLS 1-4, PROCEEDINGS | 2007年

关键词：

independent component analysis; wavelet transform; Sound Source; time-frequency analysis;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

It is well known that Independent Component. Analysis (ICA) is a useful method for blind source separation although it does have some drawbacks, such as performing poorly on unsteady sounds. In this study, in order to improve this de deficiency, a new method combining ICA with the cony-Vex discrete wavelet transform is proposed and verification of source separation with relation to the problems of permutation and scaling in the ICA are performed Through comparison of the results according to the Signal Noise Ratio (SNR), the effectiveness of the proposed method is confirmed.

引用

页码：549 / +

页数：2

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