Multisynchronization of multistable stochastic neural networks (MSNNs) is investigated herein. First, an MSNN multistable stochastic neural network (SNN) model subject to both time-varying delays and parameter uncertainties is constructed, which accurately describes neural dynamics in realistic environments. Subsequently, to reduce control costs, a coupled impulsive control strategy is adopted for studying the multisynchronization problem among MSNN systems. By developing an appropriate Lyapunov functional and leveraging the average impulsive interval concept, sufficient conditions for multisynchronization of the considered SNNs under both fixed and switching topologies are derived. Finally, the effectiveness of the proposed control scheme is verified through a numerical example.
Li et al. (Thu,) studied this question.