Adaptive finite-time synchronization of stochastic mixed time-varying delayed memristor-based neural networks

Authors：Zhang, Tianliang; Deng, Feiqi^*

Source：NEUROCOMPUTING, 2021, 452: 781-788.

DOI：10.1016/j.neucom.2019.09.117

• Finite-time synchronization
• Stochastic neural networks
• Time-delay
• Adaptive control

This paper focuses on the finite-time synchronization of stochastic memristor-based neural networks with time-varying discrete and distributed delays and discontinuous nonlinear functions via the adaptive state-feedback controller. Based on the theories of set-valued mappings and stochastic differential inclu-sions, the finite-time synchronization of the drive neural network and response neural network is trans -formed into the finite-time stabilization problem of the corresponding error stochastic neural network. By choosing an appropriate Lyapunov function and employing the theory of stochastic finite-time stabil -ity, we present a method to design the control gain parameters. Finally, an example verifies the validity of the proposed method.