Wavelet -Based Statistical Signal Processing using Hidden Markov Models

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dc.citation.bibtexNamearticleen_US
dc.citation.firstpage886
dc.citation.issueNumber4en_US
dc.citation.journalTitleIEEE Transactions on Signal Processingen_US
dc.citation.lastpage902
dc.citation.volumeNumber46en_US
dc.contributor.authorCrouse, Matthewen_US
dc.contributor.authorNowak, Robert Daviden_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.orgCenter for Multimedia Communications (http://cmc.rice.edu/)en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:40:48Z
dc.date.available2007-10-31T00:40:48Z
dc.date.issued1998-04-01en
dc.date.modified2006-06-21en_US
dc.date.submitted2001-08-25en_US
dc.descriptionJournal Paperen_US
dc.description.abstractWavelet-based statistical signal processing techniques such as denoising and detection typically model the wavelet coefficients as independent or jointly Gaussian. These models are unrealistic for many real-world signals. In this paper, we develop a new framework for statistical signal processing based on wavelet-domain hidden Markov models (HMMs). The framework enables us to concisely model the statistical dependencies and non-Gaussian Statistics encountered with real-world signals. Wavelet-domain HMMs are designed with the intrinsic properties of the wavelet transform in mind and provide powerful yet tractable probabilistic signal modes. Efficient Expectation Maximization algorithms are developed for fitting the HMMs to observational signal data. The new framework is suitable for a wide range of applications, including signal estimation, detection, classification, prediction, and even synthesis. To demonstrate the utility of wavelet-domain HMMs, we develop novel algorithms for signal denoising, classificaion, and detection.en_US
dc.description.sponsorshipOffice of Naval Researchen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.identifier.citationM. Crouse, R. D. Nowak and R. G. Baraniuk, "Wavelet -Based Statistical Signal Processing using Hidden Markov Models," <i>IEEE Transactions on Signal Processing,</i> vol. 46, no. 4, 1998.
dc.identifier.doihttp://dx.doi.org/10.1109/78.668544en_US
dc.identifier.urihttps://hdl.handle.net/1911/19815
dc.language.isoeng
dc.subjecthidden Markov models (HMMs)*
dc.subjectExpectation Maximization (EM)*
dc.subjectGaussian*
dc.subject.keywordhidden Markov models (HMMs)en_US
dc.subject.keywordExpectation Maximization (EM)en_US
dc.subject.keywordGaussianen_US
dc.titleWavelet -Based Statistical Signal Processing using Hidden Markov Modelsen_US
dc.typeJournal article
dc.type.dcmiText
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