A fast reconstruction algorithm for deterministic compressive sensing using second order reed-muller codes
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2008
Authors
Howard, S.
Calderbank, A.
Searle, S.J.
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Conference paper
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CISS 2008, 42nd Annual Conference on Information Sciences and Systems, 2008, pp.11-15
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Annual Conference on Information Sciences and Systems (19 Mar 2008 - 21 Mar 2008 : Princeton, NJ, United States)
Abstract
This paper proposes a deterministic compressed sensing matrix that comes by design with a very fast reconstruction algorithm, in the sense that its complexity depends only on the number of measurements n and not on the signal dimension N. The matrix construction is based on the second order Reed- Muller codes and associated functions. This matrix does not have RIP uniformly with respect to all k-sparse vectors, but it acts as a near isometry on k-sparse vectors with very high probability.
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