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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Communication dans un congrès
Rémi Gribonval. SPARS'09 - Signal Processing with Adaptive Sparse Structured Representations, Apr 2009, Saint Malo, France. 2009
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F. Martinelli, J.L. Sanz. Sparse representations versus the matched filter. Rémi Gribonval. SPARS'09 - Signal Processing with Adaptive Sparse Structured Representations, Apr 2009, Saint Malo, France. 2009. 〈inria-00369604〉

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