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GLOBECOM
2006
IEEE

Distributed Bayesian Fault diagnosis in Collaborative Wireless Sensor Networks

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Distributed Bayesian Fault diagnosis in Collaborative Wireless Sensor Networks
Abstract— In this contribution, we propose an efficient collaborative strategy for online change detection, in a distributed sensor network. The collaborative strategy ensures the efficiency and the robustness of the data processing, while limiting the required communication bandwith. The observed systems are assumed to have each a finite set of states, including the abrupt change behavior. For each discrete state, an observed system is assumed to evolve according to a linear state-space model. An efficient Rao-Blackwellized collaborative particle filter (RBCPF) is proposed to estimate the a posteriori probability of the discrete states of the observed systems. The Rao-Blackwellization procedure combines a sequential Monte Carlo filter with a bank of distributed Kalman filters. Only sufficient statistics are communicated between smart nodes. The spatio-temporal selection of the leader node and its collaborators is based on a trade-off between error propagation, communication ...
Hichem Snoussi, Cédric Richard
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where GLOBECOM
Authors Hichem Snoussi, Cédric Richard
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