On the exponential convergence of Matching Pursuits in quasi-incoherent dictionaries
Résumé
The purpose of this correspondence is to extend results by Villemoes and Temlyakov about exponential convergence of Matching Pursuit (MP) with some structured dictionaries for "simple" functions in finite or infinite dimension. The results are based on an extension of Tropp's results about Orthogonal Matching Pursuit (OMP) in finite dimension, with the observation that it does not only work for OMP but also for MP. The main contribution is a detailed analysis of the approximation and stability properties of MP with quasi-incoherent dictionaries, and a bound on the number of steps sufficient to reach an error no larger than a penalization factor times the best m-term approximation error.
Mots clés
- sparse matrices
- time-frequency analysis
- numerical stability
- iterative methods
- image processing
- greedy algorithms
- approximation theory
- stability property
- sparse representation
- quasiincoherent dictionary
- orthogonal matching pursuit
- nonlinear approximation
- greedy algorithm
- finite dimension
- exponential convergence
- approximation error
- OMP
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