TY - GEN

T1 - The embedded triangles algorithm for distributed estimation in sensor networks

AU - Delouille, V.

AU - Neelamani, R.

AU - Chandrasekaran, V.

AU - Baraniuk, R. G.

N1 - Publisher Copyright:
© 2003 IEEE.

PY - 2003

Y1 - 2003

N2 - 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 3x3 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.

AB - 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 3x3 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.

KW - Computational modeling

KW - Concurrent computing

KW - Embedded computing

KW - Energy efficiency

KW - Fault tolerance

KW - Graphical models

KW - Hidden Markov models

KW - Iterative algorithms

KW - Matrix decomposition

KW - Wireless sensor networks

UR - http://www.scopus.com/inward/record.url?scp=84948691099&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84948691099&partnerID=8YFLogxK

U2 - 10.1109/SSP.2003.1289422

DO - 10.1109/SSP.2003.1289422

M3 - Conference contribution

AN - SCOPUS:84948691099

T3 - IEEE Workshop on Statistical Signal Processing Proceedings

SP - 371

EP - 374

BT - Proceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE Workshop on Statistical Signal Processing, SSP 2003

Y2 - 28 September 2003 through 1 October 2003

ER -