Finite-Time Synchronization of Fractional-Order Fuzzy Time-Varying Coupled Neural Networks Subject to Reaction-Diffusion

In this article, finite-time synchronization is investigated for fractional-order fuzzy time-varying coupled neural networks subject to reaction-diffusion by establishing a new framework under fuzzy-based feedback control and fuzzy-based adaptive control. For the considered networks, we put forward an innovative graph-theory-based time-varying Lyapunov function. To overcome the difficulty of estimating the fractional derivative of this function, this article proposes a novel fractional derivative rule. Through graph theory and the Lyapunov method, several finite-time synchronous criteria are obtained for the considered networks, and the estimation of the settling time is derived. Finally, the numerical results are shown to demonstrate the practicability of the given results.

Automated summary

This article investigates finite-time synchronization for fractional-order fuzzy time-varying coupled neural networks subject to reaction-diffusion. It establishes a new framework under fuzzy-based feedback control and fuzzy-based adaptive control, and proposes an innovative graph-theory-based time-varying Lyapunov function. Through graph theory and the Lyapunov method, several finite-time synchronous criteria are obtained, and the estimation of the settling time is derived.