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2004
Springer

Blind Deconvolution of SISO Systems with Binary Source Based on Recursive Channel Shortening

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Blind Deconvolution of SISO Systems with Binary Source Based on Recursive Channel Shortening
We treat the problem of Blind Deconvolution of Single Input - Single Output (SISO) systems with real or complex binary sources. We explicate the basic mathematical idea by focusing on the noiseless case. Our approach leads to a recursive channel shortening algorithm based on simple data gouping. The channel shortening process eventually results in an instantaneous binary system with trivial solution. The method is both deterministic and very fast. It does not involve any iterative optimization or stochastic approximation procedure. It does however, require su ciently large datasets in order to meet the source richness condition.
Konstantinos I. Diamantaras, Theophilos Papadimitr
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where ICA
Authors Konstantinos I. Diamantaras, Theophilos Papadimitriou
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