Optimum Quadratic Detection and Estimation Using Generalized Joint Signal Representations

Simple item page
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.accessioned2007-10-31T01:04:07Z
dc.date.available2007-10-31T01:04:07Z
dc.date.issued1996-12-01en
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.
dc.identifier.doihttp://dx.doi.org/10.1109/78.553477en_US
dc.identifier.urihttps://hdl.handle.net/1911/20327
dc.language.isoeng
dc.subjectdetection*
dc.subjectestimation*
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 article
dc.type.dcmiText
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Say1996Dec1OptimumQua.PS
Size:
572.11 KB
Format:
Postscript Files
Download
Collections
ECE Publications
DSP Publications