Enhanced Pseudo Power Signatures for Nonstationary Signal Classification: The Projector Approach

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dc.citation.bibtexNamearticleen_US
dc.citation.journalTitleIEEE Transactions on Signal Processingen_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.accessioned2007-10-31T01:08:03Z
dc.date.available2007-10-31T01:08:03Z
dc.date.issued1999-05-01en
dc.date.modified2004-11-04en_US
dc.date.submitted2004-01-09en_US
dc.descriptionJournal Paperen_US
dc.description.abstractThe classification of nonstationary signals of unknown duration is of great importance in areas like oil exploration, moving target detection, and pattern recognition. In an earlier work, we provided a solution to this problem, based on the wavelet transform, by defining representations called <i>pseudo power signatures</i> for signal classes which were independent of signal length, location and magnitude, and proposed a simple approach using the Singular Value Decomposition to generate these signatures. This paper offers a new approach resulting in more discriminating signatures. The enhanced signatures are obtained by solving a nonlinear minimization problem involving an inverse projection. The problem formulation, solution procedure, and computational algorithm are presented in this work. An analysis of the projection signatures, and their efficacy in separating highly correlated signal classes are demonstrated through simulation examples.en_US
dc.identifier.citationV. Venkatachalam and J. Aravena, "Enhanced Pseudo Power Signatures for Nonstationary Signal Classification: The Projector Approach," <i>IEEE Transactions on Signal Processing,</i> 1999.
dc.identifier.urihttps://hdl.handle.net/1911/20413
dc.language.isoeng
dc.subjectpseudo power signatures*
dc.subjectsingular value decomposition*
dc.subject.keywordpseudo power signaturesen_US
dc.subject.keywordsingular value decompositionen_US
dc.subject.otherTime Frequency and Spectral Analysisen_US
dc.titleEnhanced Pseudo Power Signatures for Nonstationary Signal Classification: The Projector Approachen_US
dc.typeJournal article
dc.type.dcmiText
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