Thomas PEEL – Matching Pursuit with Stochastic Selection
Date(s) : 13/09/2012 iCal
14h00 - 15h00
Matching pursuit with stochastic selection (by Thomas Peel, LIF). We propose a Stochastic Selection strategy that ac- celerates the atom selection step of Matching Pursuit. This strategy consists of randomly selecting a subset of atoms and a subset of rows in the full dictionary at each step of the Matching Pursuit to obtain a sub-optimal but fast atom selection. We study the performance of the proposed algorithm in terms of approximation accuracy (decrease of the residual norm)\, of exact-sparse recovery and of audio declipping of real data. Numerical experiments show the relevance of the ap- proach. The proposed Stochastic Selection strategy is presented with Matching Pursuit but applies to any pursuit algorithms provided that their selection step is based on the computation of correlations.
Emplacement
I2M Chateau-Gombert - CMI
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