deposit_your_work

Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes

Files in this item

Files Size Format View
Wil2001Apr13Multireso.PDF 154.6Kb application/pdf Thumbnail
Wil2001Apr13Multireso.PS 253.0Kb application/postscript View/Open

Show simple item record

Item Metadata

dc.contributor.author Willett, Rebecca
dc.creator Willett, Rebecca
dc.date.accessioned 2007-10-31T01:09:45Z
dc.date.available 2007-10-31T01:09:45Z
dc.date.issued 2001-04-20
dc.date.submitted 2002-04-30
dc.identifier.uri http://hdl.handle.net/1911/20447
dc.description Elec 599 Project Report
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.
dc.language.iso eng
dc.subject Poisson
multiscale
polynomial
dc.subject.other Wavelet based Signal/Image Processing
Multiscale Methods
dc.title Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes
dc.type Elec 599 Project Report
dc.citation.bibtexName misc
dc.citation.journalTitle None
dc.date.modified 2002-04-30
dc.contributor.center Digital Signal Processing (http://dsp.rice.edu/)
dc.subject.keyword Poisson
multiscale
polynomial
dc.type.dcmi Text
dc.identifier.citation R. Willett, "Multiresolution Intensity Estimation of Piecewise Linear Poisson Processes," None, 2001.

This item appears in the following Collection(s)

  • ECE Publications [1043 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.