Direct delay decomposition approach to synchronization of chaotic fuzzy cellular neural networks with discrete, unbounded distributed delays and Markovian jumping parameters

M. Kalpana, P. Balasubramaniam and K. Ratnavelu

Applied Mathematics and Computation, 2015, vol. 254, issue C, 291-304

Abstract: In this paper, the problem of synchronization of chaotic fuzzy cellular neural networks (FCNNs) with discrete, unbounded distributed delays and Markovian jumping parameters (MJPs) is investigated. Sufficient delay-dependent stability criteria are obtained in terms of linear matrix inequalities (LMIs) to ensure the chaotic delayed FCNNs to be stochastic asymptotically synchronous with the help of free-weighting matrix and some inequality techniques. The information of the delayed plant states can be taken into full consideration. Here, the delay interval is decomposed into two subintervals by using the tuning parameter ς such that 0<ς<1. By developing a delay decomposition approach and constructing suitable Lyapunov–Krasovskii functional (LKF), sufficient conditions for synchronization are established for each subinterval. Numerical example and its simulations are provided to demonstrate the effectiveness and less conservatism of the derived results.

Keywords: Chaos; Fuzzy cellular neural networks; Linear matrix inequality; Markovian jumping parameters; Synchronization (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:254:y:2015:i:c:p:291-304

DOI: 10.1016/j.amc.2014.12.133

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