Optimum Quadratic Detection and Estimation Using Generalized Joint Signal Representations

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dc.citation.bibtexNamearticleen_US
dc.citation.journalTitleIEEE Transactions on Signal Processingen_US
dc.contributor.authorSayeed, Akbar M.en_US
dc.contributor.authorJones, Douglas L.en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T01:04:07Zen_US
dc.date.available2007-10-31T01:04:07Zen_US
dc.date.issued1996-12-01en_US
dc.date.modified2004-11-08en_US
dc.date.submitted2004-11-08en_US
dc.descriptionJournal Paperen_US
dc.description.abstractTime-frequency analysis has recently undergone significant advances in two main directions: statistically optimized methods that extend the scope of time-frequency-based techniques from merely exploratory data analysis to more quantitative application, and generalized joint signal representations that extend time-frequency-based methods to a richer class of nonstationary signals. This paper fuses the two advances by developing statistically optimal detection and estimation techniques based on generalized joint signal representations. By generalizing the statistical methods developed for time-frequency representations to arbitrary joint signal representations, this paper develops a unified theory applicable to a wide variety of problems in nonstationary statistical signal processing.en_US
dc.identifier.citationA. M. Sayeed and D. L. Jones, "Optimum Quadratic Detection and Estimation Using Generalized Joint Signal Representations," <i>IEEE Transactions on Signal Processing,</i> 1996.en_US
dc.identifier.doihttp://dx.doi.org/10.1109/78.553477en_US
dc.identifier.urihttps://hdl.handle.net/1911/20327en_US
dc.language.isoengen_US
dc.subjectdetectionen_US
dc.subjectestimationen_US
dc.subject.keyworddetectionen_US
dc.subject.keywordestimationen_US
dc.subject.otherTime Frequency and Spectral Analysisen_US
dc.titleOptimum Quadratic Detection and Estimation Using Generalized Joint Signal Representationsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
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