DocumentCode :
468961
Title :
Blind source separation by combining indepandent component analysis with complex discrete wavelet transform
Author :
Zhang, Zhong ; Enomoto, Takeshi ; Miyake, Tetsuo ; Imamura, Takashi
Author_Institution :
Toyohashi Univ. of Technol., Toyohashi
Volume :
2
fYear :
2007
fDate :
2-4 Nov. 2007
Firstpage :
549
Lastpage :
554
Abstract :
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 deficiency, a new method combining ICA with the complex 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.
Keywords :
blind source separation; discrete wavelet transforms; independent component analysis; ICA; blind source separation; complex discrete wavelet transform; independent component analysis; signal noise ratio; Acoustic noise; Blind source separation; Convolution; Discrete wavelet transforms; Fourier transforms; Frequency; Independent component analysis; Pattern analysis; Source separation; Wavelet analysis; Independent component analysis; sound source; time-frequency analysis; wavelet transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1065-1
Electronic_ISBN :
978-1-4244-1066-8
Type :
conf
DOI :
10.1109/ICWAPR.2007.4420731
Filename :
4420731
Link To Document :
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