Nonlinear approximation with dictionaries. I. Direct estimates.

Rémi Gribonval 1 Morten Nielsen 2
1 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We study various approximation classes associated with m-term approximation by elements from a (possibly redundant) dictionary in a Banach space. The standard approximation class associated with the best m-term approximation is compared to new classes defined by considering m-term approximation with algorithmic constraints: thresholding and Chebychev approximation classes are studied, respectively. We consider embeddings of the Jackson type (direct estimates) of sparsity spaces into the mentioned approximation classes. General direct estimates are based on the geometry of the Banach space, and we prove that assuming a certain structure of the dictionary is sufficient and (almost) necessary to obtain stronger results. We give examples of classical dictionaries in Lp spaces and modulation spaces where our results recover some known Jackson type estimates, and discuss some new estimates they provide.
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Rémi Gribonval, Morten Nielsen. Nonlinear approximation with dictionaries. I. Direct estimates.. The Journal of Fourier Analysis and Applications, 2004, 10 (1), pp.51--71. ⟨10.1007/s00041-004-8003-5⟩. ⟨inria-00567266⟩

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