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Mathematical Problems in Engineering
Volume 2014, Article ID 670467, 8 pages
Research Article

Distributed Sampled-Data Filtering over Sensor Networks with Markovian Switching Topologies

School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China

Received 13 December 2013; Accepted 17 February 2014; Published 18 March 2014

Academic Editor: Ge Guo

Copyright © 2014 Bin Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper considers a distributed sampled-data filtering problem in sensor networks with stochastically switching topologies. It is assumed that the topology switching is triggered by a Markov chain. The output measurement at each sensor is first sampled and then transmitted to the corresponding filters via a communication network. Considering the effect of a transmission delay, a distributed filter structure for each sensor is given based on the sampled data from itself and its neighbor sensor nodes. As a consequence, the distributed sampled-data filtering in sensor networks under Markovian switching topologies is transformed into mean-square stability problem of a Markovian jump error system with an interval time-varying delay. By using Lyapunov Krasovskii functional and reciprocally convex approach, a new bounded real lemma (BRL) is derived, which guarantees the mean-square stability of the error system with a desired performance. Based on this BRL, the topology-dependent sampled-data filters are obtained. An illustrative example is given to demonstrate the effectiveness of the proposed method.