BLIND SOURCE SEPARATION USING WAVELETS

Summary

A new algorithm for blind source separation (BSS) is proposed, in which frequency-domain ICA and time- domain ICA are combined to achieve a superior source-separation performances.

Keywords

Blind signal separation, Independent component analysis, Source separation, Wavelet, Computer science

References

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Convolutive blind source separation by minimizing mutual information between segments of signalsKenneth E. Hild, Domenick J. Pinto, Deniz Erdoğmuş — 2005
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Ideal spatial adaptation by wavelet shrinkageDavid L. Donoho, Iain M. Johnstone — 1994
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SPEECH EXTRACTION FROM INTERFERENCES IN REAL ENVIRONMENT USING BANK OF FILTERS AND BLIND SOURCE SEPARATIONTomasz M. Rutkowski, A. Cichocki, A. Barros — 2000

Cited by

An adaptive approach to subband domain convolutive blind source separationSara Ayub, Muhammad Arslan, Muhammad Salman — 2015
Singing-voice separation from monaural recordings using empirical wavelet transformAnuja R. Nerkar, Madhuri A. Joshi — 2016
Blind Source separation and Echo cancellation using Discreet Wavelet transform and ICAS. Yadav, Meena Chavan — 2015
PERFORMANCE ANALYSIS OF SUB AND SUPER-GAUSSIAN BLIND AUDIO SOURCE SEPARATIONAkhil Arora, R. Mehra, Naveen Dubey — 2015
Decorrelation of Lung and Heart SoundA. A. Ballewar — 2015

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