Synchronization of non-identical chaotic delayed fuzzy cellular neural networks based on sliding mode control

–In this paper, we investigate the synchronization problems of chaotic fuzzy cellular neural networks with time-varying delays. To overcome the difficulty that complete synchronization between non-identical chaotic neural networks cannot be achieved only by utilizing output feedback control, we use a sliding mode control approach to study the synchronization of non-identical chaotic fuzzy cellular neural networks with time-varying delays, where the parameters and activation functions are mismatched. This research demonstrates the effectiveness of application in secure communication. Numerical simulations are carried out to illustrate the main results.

► We explore the issues of integrating mismatched parameters and neuron activation functions into the study of synchronization for fuzzy cellular neural networks. ► Sliding mode controller to guarantee the synchronization for non-identical chaotic fuzzy cellular neural networks is obtained. ► Numerical simulations are carried out to demonstrate the effectiveness of the main results.