Optimal wavelets for signal decomposition and the existence of scale limited signals

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dc.citation.bibtexNametechreport
dc.citation.issueNumberCML TR91-07
dc.citation.journalTitleNone
dc.contributor.authorOdegard, Jan E.
dc.contributor.authorGopinath, Ramesh A.
dc.contributor.authorBurrus, C. Sidney
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)
dc.contributor.orgCML (http://cml.rice.edu/)
dc.date.accessioned2007-10-31T00:56:39Z
dc.date.available2007-10-31T00:56:39Z
dc.date.issued1992-01-15
dc.date.modified2004-04-19
dc.date.submitted2004-04-19
dc.descriptionTech Report
dc.description.abstractWavelet methods give a flexible alternative to Fourier methods in non-stationary signal analysis. The concept of <i>band-limitedness</i> plays a fundamental role in Fourier analysis. Since wavelet theory replaces <i>frequency</i> with <i>scale</i>, a natural question is whether there exists a useful concept of <i>scale-limitedness</i>. Obvious definitions of scale-limitedness are too restrictive, in that there would be few or no useful scale-limited signals. This paper introduces a viable definition for scale-limited signals, and shows that the class is rich enough to include bandlimited signals, and impulse trains, among others. Moreover, for a wide choice of criteria, we show how to design the optimal wavelet for representing a given signal, and how to design <i>robust</i> wavelets that optimally represent certain classes of signals.
dc.identifier.citationJ. E. Odegard, R. A. Gopinath and C. S. Burrus, "Optimal wavelets for signal decomposition and the existence of scale limited signals," <i>None,</i> no. CML TR91-07, 1992.
dc.identifier.doihttp://dx.doi.org/10.1109/ICASSP.1992.226377
dc.identifier.urihttps://hdl.handle.net/1911/20167
dc.language.isoeng
dc.subject.keywordwavelets
dc.subject.otherWavelet based Signal/Image Processing
dc.titleOptimal wavelets for signal decomposition and the existence of scale limited signals
dc.typeReport
dc.type.dcmiText
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