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Finite/Fixed-Time Synchronization of Memristor-Based Fuzzy Neural Networks with Markov Jumping Parameters Under Unified Control Schemes

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Abstract

This paper proposes a unified framework to achieve the finite/fixed-time synchronization of memristor-based fuzzy delayed neural networks considering both Markov jumping phenomenon and external disturbance. Under the designed common controller, by regulating its main control parameters, the goals of finite-time and fixed-time synchronization for the network can be achieved separately. Besides, by integrating algebraic inequality technologies, the fuzzy set theory and Lyapunov theory, a new finite/fixed-time theorem can be obtained for the drive-response system. Taking into account more complex Lyapunov–Krasovskii functional involving mode-dependent terms and double integral terms, is more closer to practical applications than those in the existing results. Finally, an example is presented to substantiate the effectiveness of the theoretical results.

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Acknowledgements

This work was supported by the Postgraduate Research and Practice Innovation Program of Jiangsu Province (Grants KYCX21 0309).

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Authors and Affiliations

  1. School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China

    Ting Wang, Mingcheng Dai, Baoyong Zhang & Yijun Zhang

Authors
  1. Ting Wang
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  2. Mingcheng Dai
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  3. Baoyong Zhang
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  4. Yijun Zhang
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Contributions

T.W. proved the theorems. T.W. and M.D. did the simulation and wrote the main manuscript. B.Z. and Y.Z. proposed the problem under consideration and provided methods to solve the problem. All authors reviewed the manuscript.

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Correspondence to Baoyong Zhang.

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Wang, T., Dai, M., Zhang, B. et al. Finite/Fixed-Time Synchronization of Memristor-Based Fuzzy Neural Networks with Markov Jumping Parameters Under Unified Control Schemes. Neural Process Lett 55, 12525–12545 (2023). https://doi.org/10.1007/s11063-023-11431-w

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