Multichannel blind deconvolution using a novel filter decomposition method

Authors:
Bin Xia;Liqing Zhang
Affiliations:
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

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ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I

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Abstract

In our previous work [11], we introduced a filter decomposition method for blind deconvolution in non-minimum phase system. To simplify the deconvolution procedure, we further study the demixing filter and modify the cascade structure of demixing filter. In this paper, we introduce a novel two-stage algorithm for blind deconvolution. In first stage, we present a permutable cascade structure which constructed by a causal filter and an anti-causal scalar filter. Then, we develop SOS-based algorithm for causal filter and derive a natural gradient algorithm for anti-causal scalar filter. At second stage, we apply an instantaneous ICA algorithm to eliminate the residual instantaneous mixtures. Computer simulations show the validity and effectiveness of this approach.