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Hidden Markov Models for Wavelet-based Signal Processing

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dc.contributor.author Crouse, Matthew
Baraniuk, Richard G.
Nowak, Robert David
dc.creator Crouse, Matthew
Baraniuk, Richard G.
Nowak, Robert David
dc.date.accessioned 2007-10-31T00:40:41Z
dc.date.available 2007-10-31T00:40:41Z
dc.date.issued 1996-11-01
dc.date.submitted 1996-11-01
dc.identifier.uri http://hdl.handle.net/1911/19812
dc.description Conference Paper
dc.description.abstract Current wavelet-based statistical signal and image processing techniques such as shrinkage and filtering treat the wavelet coefficients as though they were statistically independent. This assumption is unrealistic; considering the statistical dependencies between wavelet coefficients can yield substantial performance improvements. In this paper we develop a new framework for wavelet-based signal processing that employs hidden Markov models to characterize the dependencies between wavelet coefficients. To illustrate the power of the new framework, we derive a new signal denoising algorithm that outperforms current scalar shrinkage techniques.
dc.language.iso eng
dc.subject.other DSP for Communications
dc.title Hidden Markov Models for Wavelet-based Signal Processing
dc.type Conference Paper
dc.date.note 2006-06-12
dc.citation.bibtexName inproceedings
dc.date.modified 2006-06-12
dc.contributor.center Digital Signal Processing (http://dsp.rice.edu/)
dc.citation.volumeNumber 2
dc.citation.pageNumber 1029-1035
dc.citation.location Pacific Grove, CA
dc.citation.conferenceName Asilomar Conference on Signals, Systems, and Computers
dc.type.dcmi Text
dc.identifier.citation M. Crouse, R. G. Baraniuk and R. D. Nowak,"Hidden Markov Models for Wavelet-based Signal Processing," in Asilomar Conference on Signals, Systems, and Computers,, pp. 1029-1035.

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  • ECE Publications [1032 items]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508 items]
    Publications by Rice Faculty and graduate students in digital signal processing.