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The Embedded Triangles Algorithm for Distributed Estimation in Sensor Networks

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Title: The Embedded Triangles Algorithm for Distributed Estimation in Sensor Networks
Author: Delouille, Veronique; Neelamani, Ramesh; Chandrasekaran, Venkat; Baraniuk, Richard G.
Type: Conference Paper
Keywords: Hidden Markov Models; distributed estimation; block Jacobi; graphical models
Citation: V. Delouille, R. Neelamani, V. Chandrasekaran and R. G. Baraniuk,"The Embedded Triangles Algorithm for Distributed Estimation in Sensor Networks," in IEEE Workshop on Statistical Signal Processing (SSP),
Abstract: We propose a new iterative distributed estimation algorithm for Gaussian hidden Markov graphical models with loops. We decompose a loopy graph into a number of linked embedded triangles and then apply a parallel block-Jacobi iteration comprising local linear minimum mean-square-error estimation on each triangle (involving a simple 3 × 3 matrix inverse computation) followed by an information exchange between neighboring nodes and triangles. A simulation study demonstrates that the algorithm converges extremely rapidly, outperforming a number of existing algorithms. Embedded triangles are simple, local, scalable, fault-tolerant, and energy-efficient, and thus ideally suited for wireless sensor networks.
Date Published: 2003-09-01

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  • ECE Publications [1030 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.