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

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  • Kalpana, M.
  • Balasubramaniam, P.
  • Ratnavelu, K.

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.

Suggested Citation

  • Kalpana, M. & Balasubramaniam, P. & Ratnavelu, K., 2015. "Direct delay decomposition approach to synchronization of chaotic fuzzy cellular neural networks with discrete, unbounded distributed delays and Markovian jumping parameters," Applied Mathematics and Computation, Elsevier, vol. 254(C), pages 291-304.
  • Handle: RePEc:eee:apmaco:v:254:y:2015:i:c:p:291-304
    DOI: 10.1016/j.amc.2014.12.133
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    References listed on IDEAS

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    1. Feng, Xiaomei & Zhang, Fengqin & Wang, Wenjuan, 2011. "Global exponential synchronization of delayed fuzzy cellular neural networks with impulsive effects," Chaos, Solitons & Fractals, Elsevier, vol. 44(1), pages 9-16.
    2. Souza, Fernando O. & Palhares, Reinaldo M. & Ekel, Petr Ya., 2009. "Novel stability criteria for uncertain delayed Cohen–Grossberg neural networks using discretized Lyapunov functional," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2387-2393.
    3. Souza, Fernando O. & Palhares, Reinaldo M. & Ekel, Petr Ya., 2009. "Improved asymptotic stability analysis for uncertain delayed state neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 39(1), pages 240-247.
    4. Yu, Juan & Hu, Cheng & Jiang, Haijun & Teng, Zhidong, 2012. "Exponential lag synchronization for delayed fuzzy cellular neural networks via periodically intermittent control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 895-908.
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    Cited by:

    1. Wang, Jun & Shi, Kaibo & Huang, Qinzhen & Zhong, Shouming & Zhang, Dian, 2018. "Stochastic switched sampled-data control for synchronization of delayed chaotic neural networks with packet dropout," Applied Mathematics and Computation, Elsevier, vol. 335(C), pages 211-230.
    2. Li, Tao & Tang, Xiaoling & Qian, Wei & Fei, Shumin, 2019. "Hybrid-delay-dependent approach to synchronization in distributed delay neutral neural networks," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 449-463.
    3. Ratnavelu, K. & Manikandan, M. & Balasubramaniam, P., 2015. "Synchronization of fuzzy bidirectional associative memory neural networks with various time delays," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 582-605.
    4. Li, Bing, 2017. "A note on stability of hybrid stochastic differential equations," Applied Mathematics and Computation, Elsevier, vol. 299(C), pages 45-57.
    5. Xie, Qian & Si, Gangquan & Zhang, Yanbin & Yuan, Yiwei & Yao, Rui, 2016. "Finite-time synchronization and identification of complex delayed networks with Markovian jumping parameters and stochastic perturbations," Chaos, Solitons & Fractals, Elsevier, vol. 86(C), pages 35-49.
    6. Li, Feng & Song, Shuai & Zhao, Jianrong & Xu, Shengyuan & Zhang, Zhengqiang, 2019. "Synchronization control for Markov jump neural networks subject to HMM observation and partially known detection probabilities," Applied Mathematics and Computation, Elsevier, vol. 360(C), pages 1-13.

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