Convolutive Blind Source Separation Applied to the Communication Signals

Xiu Ying Sun; Peng Fei Xu

doi:10.4028/www.scientific.net/AMM.263-266.188

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 263-266Convolutive Blind Source Separation Applied to the...

Convolutive Blind Source Separation Applied to the Communication Signals

Abstract:

In this paper, a method for convolutive blind separation for communication sources is introduced. The method works in time-domain, and it is based on the recently very successful algorithm EFICA for Independent Component Analysis, which is an enhanced version of more famous FastICA. In addition, an automatic method of wavelet de-noising processing is proposed, using the 'mini-maxi' soft-threshold model, wavelet decomposition is performed at level 5 for the noisy separated communication signal, it can improve the performance of BSS system, and this is confirmed in the experiment for communication signals with same carrier frequencies and modulation.

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Periodical:

Applied Mechanics and Materials (Volumes 263-266)

Pages:

188-191

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.263-266.188

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Online since:

December 2012

Authors:

Xiu Ying Sun, Peng Fei Xu

Keywords:

Communication Signals, Convolutive Mixture, Time-Domain Blind Source Separation, Wavelet Denoising

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