Synchronization of Coupled Stochastic Reaction-Diffusion Neural Networks With Multiple Weights and Delays via Pinning Impulsive Control
Zhengran Cao, Chuandong Li, Zhilong He, Xiaoyu Zhang, Le You
Abstract
The paper mainly investigates the synchronization problem of coupled stochastic reaction-diffusion neural networks with multiple weights and time delays via pinning impulsive control. Based on stochastic analysis theory, inequality technology, LMIs, and the principle of comparison, the sufficient conditions are obtained to ensure the synchronization of the coupled RDNNs with multiple weights and delays using a suitable pinning impulsive control protocol. Compared with the recent relevant theoretical research, the model established in this paper is more universal, and takes more industrial constraints into consideration. In addition, the synchronization criterion obtained in the paper has less restrictions. Finally, a numerical simulation is given to verify the correctness and feasibility of the theoretical results.