Title: A compressive sensing framework for multirate signal estimation
Abstract: This paper develops a novel compressive sensing setting for the multirate signal estimation problem. The multirate signal estimation task consists of estimating the values for a source signal when observed through several measurement channels sampled at different sampling rates. We demonstrate that this formulation can be recast in a compressive sensing setup. Reformulating the multirate signal estimation problem in a compressive sensing framework, enables us to infuse the sparse signal estimation and reconstruction methodologies into this multirate setting in a novel manner. We show that for sparse signals sampled through a multirate multichannel system, the compressive sensing signal reconstruction paradigm fits in effectively. Simulations are provided demonstrating that compressive sensing based signal reconstruction for multirate signal estimation is a viable and effective alternative.
Publication Year: 2010
Publication Date: 2010-05-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 3
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