Mathematical Biosciences and Engineering (Sep 2022)

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

  • Ruoyu Wei ,
  • Jinde Cao

DOI
https://doi.org/10.3934/mbe.2022598
Journal volume & issue
Vol. 19, no. 12
pp. 12814 – 12832

Abstract

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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.

Keywords