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Distributed state estimation for hidden Markov models by sensor networks with dynamic quantization

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2 Author(s)
Minyi Huang ; Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia ; S. Dey

This paper considers the state estimation of hidden Markov models by sensor networks. We study a network structure with feedback from the fusion center to the sensor nodes, and a dynamic quantization scheme is proposed and analyzed by a stochastic control approach. The resulting dynamic programming equation is solved by the relative value iteration algorithm. Furthermore, a dynamic rate allocation method is also proposed.

Published in:

Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004

Date of Conference:

14-17 Dec. 2004