Time Frequency Detectors

dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameConference on Information Sciences and Systemsen_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.accessioned2007-10-31T01:04:16Z
dc.date.available2007-10-31T01:04:16Z
dc.date.issued1996-01-20en
dc.date.modified2004-01-22en_US
dc.date.note2004-01-09en_US
dc.date.submitted1996-01-20en_US
dc.descriptionConference Paperen_US
dc.description.abstractTime-frequency representations (TFRs) provide a powerful and flexible structure for designing optimal detectors in a variety of nonstationary scenarios. In this paper, we describe a TFR-based framework for optimal detection of arbitrary second-order stochastic signals, with certain unknown or random nuisance parameters, in the presence of Gaussian noise. The framework provides a useful model for many important applications including machine fault diagnostics and radar/sonar. We emphasize a subspace-based formulation of such TFR detectors which can be exploited in a variety of ways to design new techniques. In particular, we explore an extension based on <i>multi-channel/sensor</i> measurements that are often available in practice to facilitate improved signal processing. In addition to potentially improved performance, the subspace-based interpretation of such multi-channel detectors provides useful information about the physical mechanisms underlying the signals of interest.en_US
dc.identifier.citationA. M. Sayeed and D. L. Jones, "Time Frequency Detectors," 1996.
dc.identifier.urihttps://hdl.handle.net/1911/20331
dc.language.isoeng
dc.subjectsecond-order stochastic signals*
dc.subjectGaussian noise*
dc.subjectmulti-channel/sensor measurements*
dc.subject.keywordsecond-order stochastic signalsen_US
dc.subject.keywordGaussian noiseen_US
dc.subject.keywordmulti-channel/sensor measurementsen_US
dc.subject.otherTime Frequency and Spectral Analysisen_US
dc.titleTime Frequency Detectorsen_US
dc.typeConference paper
dc.type.dcmiText
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