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Sparse representations versus the matched filter

Abstract : We have considered the problem of detection and estimation of compact sources immersed in a background plus instrumental noise. Sparse approximation to signals deals with the problem of finding a representation of a signal as a linear combination of a small number of elements from a set of signals called dictionary. The estimation of the signal leads to a minimization problem for the amplitude associated to the sources. We have developed a methodology that minimizes the lp-norm with a constraint on the goodness-of-fit and we have compared different norms against the matched filter.
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Submitted on : Friday, March 20, 2009 - 2:36:57 PM
Last modification on : Thursday, September 9, 2021 - 9:38:04 AM
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  • HAL Id : inria-00369604, version 1



F. Martinelli, J.L. Sanz. Sparse representations versus the matched filter. SPARS'09 - Signal Processing with Adaptive Sparse Structured Representations, Inria Rennes - Bretagne Atlantique, Apr 2009, Saint Malo, France. ⟨inria-00369604⟩



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