Signal Estimation using Wavelet-Markov Models
| dc.citation.bibtexName | inproceedings | en_US |
| dc.citation.conferenceName | IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) | en_US |
| dc.citation.firstpage | 3429 | en_US |
| dc.citation.lastpage | 3432 | en_US |
| dc.citation.location | Munich, Germany | en_US |
| dc.citation.volumeNumber | 5 | en_US |
| dc.contributor.author | Crouse, Matthew | en_US |
| dc.contributor.author | Baraniuk, Richard G. | en_US |
| dc.contributor.author | Nowak, Robert David | en_US |
| dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
| dc.date.accessioned | 2007-10-31T00:40:44Z | en_US |
| dc.date.available | 2007-10-31T00:40:44Z | en_US |
| dc.date.issued | 1997-04-01 | en_US |
| dc.date.modified | 2006-06-12 | en_US |
| dc.date.note | 2006-06-12 | en_US |
| dc.date.submitted | 1997-04-01 | en_US |
| dc.description | Conference Paper | en_US |
| 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. 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 algorithm for signal estimation in nonGaussian noise. | en_US |
| dc.identifier.citation | M. Crouse, R. G. Baraniuk and R. D. Nowak, "Signal Estimation using Wavelet-Markov Models," vol. 5, 1997. | en_US |
| dc.identifier.doi | http://dx.doi.org/10.1109/ICASSP.1997.604601 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/19813 | en_US |
| dc.language.iso | eng | en_US |
| dc.subject.other | DSP for Communications | en_US |
| dc.title | Signal Estimation using Wavelet-Markov Models | en_US |
| dc.type | Conference paper | en_US |
| dc.type.dcmi | Text | en_US |
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