Nonstationary Signal Enhancement Using The Wavelet Transform

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dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameProc. of the 28 Southeastern Symposium on System Theoryen_US
dc.contributor.authorVenkatachalam, Vidyaen_US
dc.contributor.authorAravena, Jorge.L.en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T01:07:50Z
dc.date.available2007-10-31T01:07:50Z
dc.date.issued1996-03-20en
dc.date.modified2004-01-09en_US
dc.date.note2004-01-09en_US
dc.date.submitted1996-03-20en_US
dc.descriptionConference Paperen_US
dc.description.abstractConventional signal processing typically involves frequency selective techniques which are highly inadequate for nonstationary signals. In this paper, we present an approach to perform time-frequency selective processing using the Wavelet Transform. The approach is motivated by the excellent localization, in both time and frequency, afforded by the wavelet basis functions. Suitably chosen wavelet basis functions are used to characterize the subspace of signals that have a given localized time-frequency support, thus enabling a time-frequency partitioning of signals. A practical implementation scheme using filter banks is also presented, and the effectiveness of the approach over conventional techniques is demonstrated.en_US
dc.identifier.citationV. Venkatachalam and J. Aravena, "Nonstationary Signal Enhancement Using The Wavelet Transform," 1996.
dc.identifier.doihttp://dx.doi.org/10.1109/SSST.1996.493479en_US
dc.identifier.urihttps://hdl.handle.net/1911/20408
dc.language.isoeng
dc.subjectTemporary*
dc.subject.keywordTemporaryen_US
dc.subject.otherTime Frequency and Spectral Analysisen_US
dc.titleNonstationary Signal Enhancement Using The Wavelet Transformen_US
dc.typeConference paper
dc.type.dcmiText
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