Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes
| dc.citation.bibtexName | misc | en_US |
| dc.citation.journalTitle | None | en_US |
| dc.contributor.author | Willett, Rebecca | en_US |
| dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
| dc.date.accessioned | 2007-10-31T01:09:45Z | en_US |
| dc.date.available | 2007-10-31T01:09:45Z | en_US |
| dc.date.issued | 2001-04-20 | en_US |
| dc.date.modified | 2002-04-30 | en_US |
| dc.date.submitted | 2002-04-30 | en_US |
| dc.description | Elec 599 Project Report | en_US |
| dc.description.abstract | Given observations of a one-dimensional piecewise linear, length-M Poisson intensity function, our goal is to estimate both the partition points and the parameters of each segment. In order to determine where the breaks lie, we develop a maximum penalized likelihood estimator based on information-theoretic complexity penalization. We construct a probabilistic model of the observations within a multiscale framework, and use this framework to devise a computationally efficient optimization algorithm, based on a tree-pruning approach, to compute the MPLE. | en_US |
| dc.identifier.citation | R. Willett, "Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes," <i>None,</i> 2001. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/20447 | en_US |
| dc.language.iso | eng | en_US |
| dc.subject | Poisson | en_US |
| dc.subject | multiscale | en_US |
| dc.subject | polynomial | en_US |
| dc.subject.keyword | Poisson | en_US |
| dc.subject.keyword | multiscale | en_US |
| dc.subject.keyword | polynomial | en_US |
| dc.subject.other | Wavelet based Signal/Image Processing | en_US |
| dc.subject.other | Multiscale Methods | en_US |
| dc.title | Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes | en_US |
| dc.type | Report | en_US |
| dc.type.dcmi | Text | en_US |