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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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https://hal.inria.fr/inria-00369604
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Submitted on : Friday, March 20, 2009 - 2:36:57 PM
Last modification on : Saturday, December 26, 2020 - 1:46:05 PM
Long-term archiving on: : Friday, October 12, 2012 - 2:01:51 PM

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  • HAL Id : inria-00369604, version 1

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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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