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Conference Papers Year : 2009

Sparsity Measure and the Detection of Significant Data

Abstract

The paper provides a formal description of the sparsity of a representation via the detection thresholds. The formalism proposed derives from theoretical results about the detection of significant coefficients when data are observed in presence of additive white Gaussian noise. The detection thresholds depend on two parameters describing the sparsity degree for the representation of a signal. The standard universal and minimax thresholds correspond to detection thresholds associated with different sparsity degrees.
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Dates and versions

inria-00369628 , version 1 (20-03-2009)

Identifiers

  • HAL Id : inria-00369628 , version 1

Cite

Abdourrahmane Atto, Dominique Pastor, Grégoire Mercier. Sparsity Measure and the Detection of Significant Data. SPARS'09 - Signal Processing with Adaptive Sparse Structured Representations, Inria Rennes - Bretagne Atlantique, Apr 2009, Saint Malo, France. ⟨inria-00369628⟩
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