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Novel stability condition of stochastic fuzzy neural networks with Markovian jumping under impulsive perturbations

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Abstract

For the first time, this paper investigates the global asymptotic stability of stochastic fuzzy neural networks with mixed delays and Markovian jumping under impulsive perturbations in mean square. The mixed delays include time-varying delay and continuously distributed delay. By using stochastic analysis method, linear convex combination technique, Jensen integral inequality and the free-weight matrix method, a novel sufficient condition is derived to ensure the global asymptotic stability of the equilibrium point of the considered networks in mean square. The proposed result, which is expressed in terms of linear matrix inequalities, can be easily checked via Matlab software. Finally, a numerical example is given to demonstrate the effectiveness and less conservativeness of our theoretical results over existing literature.

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Authors and Affiliations

  1. School of Science, Dalian Jiaotong University, 116028, Dalian, People’s Republic of China

    Cheng-De Zheng & Yanli Zhang

  2. School of Information Science and Engineering, Northeastern University, 110004, Shenyang, People’s Republic of China

    Zhanshan Wang

Authors
  1. Cheng-De Zheng
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  2. Yanli Zhang
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  3. Zhanshan Wang
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Corresponding author

Correspondence to Cheng-De Zheng.

Additional information

This work was supported by the National Natural Science Foundation of China 61034005, 61074073, 61273022, Program for New Century Excellent Talents in University of China (NCET-10-0306), and the Fundamental Research Funds for the Central Universities under Grants N110504001 and N100104102.

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Zheng, CD., Zhang, Y. & Wang, Z. Novel stability condition of stochastic fuzzy neural networks with Markovian jumping under impulsive perturbations. Int. J. Mach. Learn. & Cyber. 7, 795–803 (2016). https://doi.org/10.1007/s13042-014-0298-1

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  • DOI: https://doi.org/10.1007/s13042-014-0298-1

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