Best bases for signal spaces

Translated title of the contribution: Best bases for signal spaces

Yonathan Aflalo, Haïm Brezis, Alfred Bruckstein, Ron Kimmel, Nir Sochen

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


We discuss the topic of selecting optimal orthonormal bases for representing classes of signals defined either through statistics or via some deterministic characterizations, or combinations of the two. In all cases, the best bases result from spectral analysis of a Hermitian matrix that summarizes the prior information we have on the signals we want to represent, achieving optimal progressive approximations. We also provide uniqueness proofs for the discrete cases.

Translated title of the contributionBest bases for signal spaces
Original languageEnglish
Pages (from-to)1155-1167
Number of pages13
JournalComptes Rendus Mathematique
Issue number12
StatePublished - 1 Dec 2016


FundersFunder number
National Science Foundation238702, DMS-1207793
European Commission
European Research Council267414


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