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Prespecified-time bipartite synchronization of coupled reaction-diffusion memristive neural networks with competitive interactions


  • Received: 01 June 2022 Revised: 25 July 2022 Accepted: 27 July 2022 Published: 01 September 2022
  • In this paper, we investigate the prespecified-time bipartite synchronization (PTBS) of coupled reaction-diffusion memristive neural networks (CRDMNNs) with both competitive and cooperative interactions. Two types of bipartite synchronization are considered: leaderless PTBS and leader-following PTBS. With the help of a structural balance condition, the criteria for PTBS for CRDMNNs are derived by designing suitable Lyapunov functionals and novel control protocols. Different from the traditional finite-time or fixed-time synchronization, the settling time obtained in this paper is independent of control gains and initial values, which can be pre-set according to the task requirements. Lastly, numerical simulations are given to verify the obtained results.

    Citation: Ruoyu Wei, Jinde Cao. Prespecified-time bipartite synchronization of coupled reaction-diffusion memristive neural networks with competitive interactions[J]. Mathematical Biosciences and Engineering, 2022, 19(12): 12814-12832. doi: 10.3934/mbe.2022598

    Related Papers:

  • In this paper, we investigate the prespecified-time bipartite synchronization (PTBS) of coupled reaction-diffusion memristive neural networks (CRDMNNs) with both competitive and cooperative interactions. Two types of bipartite synchronization are considered: leaderless PTBS and leader-following PTBS. With the help of a structural balance condition, the criteria for PTBS for CRDMNNs are derived by designing suitable Lyapunov functionals and novel control protocols. Different from the traditional finite-time or fixed-time synchronization, the settling time obtained in this paper is independent of control gains and initial values, which can be pre-set according to the task requirements. Lastly, numerical simulations are given to verify the obtained results.



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