A constrained MDP approach to dynamic quantizer design for HMM state estimation
IEEE Transactions on Signal Processing
Transmission rate allocation in multisensor target tracking over a shared network
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper considers the state estimation of hidden Markov models by sensor networks. The objective is to minimize the long term average of the mean square estimation error for the underlying finite state Markov chain. By employing feedback from the fusion center, a dynamic quantization scheme for the sensor nodes is proposed and analyzed by a stochastic control approach. Dynamic rate allocation is also considered when the sensor nodes generate mode dependent measurements