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dc.contributor.authorCohen, Albert
HAL ID: 12723
dc.date.accessioned2014-07-10T08:26:32Z
dc.date.available2014-07-10T08:26:32Z
dc.date.issued1994
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/13695
dc.language.isoenen
dc.subjectnon-stationary processen
dc.subjectMultiscale Analysisen
dc.subject.ddc519en
dc.titleNon-stationary Multiscale Analysisen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenOrthonormal bases of wavelets and wavelet packets yield linear, non-redundant time-scale and time-frequency decompositions for arbitrary functions and signals. Numerically, these decompositions are based on the iterative application of digital filter banks. Usually these filters are the same at every iteration. We show here the advantages of using filters that may vary from one iteration to the next one. An appropriate choice leads to C∞ compactly supported wavelets and allows a better control of the time-frequency localization properties of wavelet packets. These results have been obtained jointly with N. Dyn of Tel-Aviv University and E. Séré of CEREMADE.en
dc.relation.isversionofjnlnameWavelet Analysis and Its Applications
dc.relation.isversionofjnlvol5en
dc.relation.isversionofjnldate1994
dc.relation.isversionofjnlpages3-12en
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/B978-0-08-052084-1.50006-5en
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen


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