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dc.contributor.authorDelouille, Veronique
Neelamani, Ramesh
Baraniuk, Richard G.
dc.creatorDelouille, Veronique
Neelamani, Ramesh
Baraniuk, Richard G.
dc.date.accessioned 2007-10-31T00:42:39Z
dc.date.available 2007-10-31T00:42:39Z
dc.date.issued 2004-04-01
dc.date.submitted 2004-04-01
dc.identifier.urihttp://hdl.handle.net/1911/19855
dc.description Conference Paper
dc.description.abstract We propose a new iterative distributed algorithm for linear minimum mean-squared-error (LMMSE) estimation in sensor networks whose measurements follow a Gaussian hidden Markov graphical model with cycles. The embedded polygons algorithm decomposes a loopy graphical model into a number of linked embedded polygons and then applies a parallel block Gauss-Seidel iteration comprising local LMMSE estimation on each polygon (involving inversion of a small matrix) followed by an information exchange between neighboring nodes and polygons. The algorithm is robust to temporary communication faults such as link failures and sleeping nodes and enjoys guaranteed convergence under mild conditions. A simulation study indicates that energy consumption for iterative estimation increases substantially as more links fail or nodes sleep. Thus, somewhat surprisingly, energy conservation strategies such as low-powered transmission and aggressive sleep schedules could actually be counterproductive.
dc.language.iso eng
dc.subjectSensor networks
distributed estimation
graphical models
hidden Markov models
Wiener filter
matrix splitting distributed estimation
graphical models
hidden Markov models
Wiener filter
matrix splitting
dc.subject.otherSignal Processing Applications
dc.title Robust Distributed Estimation in Sensor Networks using the Embedded Polygons Algorithm
dc.type Conference paper
dc.date.note 2004-03-03
dc.citation.bibtexName inproceedings
dc.date.modified 2006-06-20
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)
dc.subject.keywordSensor networks
distributed estimation
graphical models
hidden Markov models
Wiener filter
matrix splitting distributed estimation
graphical models
hidden Markov models
Wiener filter
matrix splitting
dc.citation.location Berkeley, CA
dc.citation.conferenceName Information Processing in Sensor Networks
dc.type.dcmi Text
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1145/984622.984681
dc.citation.firstpage 405
dc.citation.lastpage 413
dc.identifier.citation V. Delouille, R. Neelamani and R. G. Baraniuk, "Robust Distributed Estimation in Sensor Networks using the Embedded Polygons Algorithm," 2004.


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  • ECE Publications [1212]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.

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