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Title:
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The Embedded Triangles Algorithm for Distributed Estimation in Sensor Networks |
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Author:
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Delouille, Veronique; Neelamani, Ramesh; Chandrasekaran, Venkat; Baraniuk, Richard G.
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Type:
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Conference Paper |
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Keywords:
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Hidden Markov Models; distributed estimation; block Jacobi; graphical models |
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Citation:
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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), |
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Abstract:
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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. |
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Date Published:
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2003-09-01 |
