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<p>In this paper, we propose some simple control strategies to solve the fixed-time (FXT) and predefined-time (PDT) synchronization problems of fuzzy memristive neural networks (FMNNs) under stochastic disturbances. First, for stochastic nonlinear systems, we present a new generalized FXT stability lemma which provides a more flexible framework for the analysis of stochastic FXT stability, where the stochastic noise can play a positive role to facilitate the FXT stability of system and thus breaks the imitation of earlier works where the stochastic noise was considered an unfavorable factor affecting. Subsequently, by designing suitable controllers, some sufficient conditions for achieving FXT and PDT synchronization of considered FMNNs under stochastic disturbances are derived. Finally, numerical simulations verify the validity of the theoretical results.</p>

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Fixed/predefined-time synchronization for fuzzy memristive neural networks under stochastic perturbations via convex analysis

  • 期刊论文

  • 发表日期：

    2026年3月20日

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  • Gang Wang,
  • Abdujelil Abdurahman

摘要

In this paper, we propose some simple control strategies to solve the fixed-time (FXT) and predefined-time (PDT) synchronization problems of fuzzy memristive neural networks (FMNNs) under stochastic disturbances. First, for stochastic nonlinear systems, we present a new generalized FXT stability lemma which provides a more flexible framework for the analysis of stochastic FXT stability, where the stochastic noise can play a positive role to facilitate the FXT stability of system and thus breaks the imitation of earlier works where the stochastic noise was considered an unfavorable factor affecting. Subsequently, by designing suitable controllers, some sufficient conditions for achieving FXT and PDT synchronization of considered FMNNs under stochastic disturbances are derived. Finally, numerical simulations verify the validity of the theoretical results.