Work

Sparsity Measure and the Detection of Significant Data

Year: 2009

Type: conference-paper

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. Index Terms—Sparsity measure, Wavelets, Detection thresholds. I.

Authors: Abdourrahmane M. Atto, Dominique Pastor, Grégoire Mercier

Language: English

Topic: Sparse and Compressive Sensing Techniques

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2954465958

FWCI:

Cites: 7

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Related to: 10