Exponential Synchronization‐Like Control of State‐Dependent Impulsive Chaotic Neural Networks

ABSTRACT This paper investigates the local exponential synchronization‐like control between state‐dependent impulsive chaotic neural networks. First, various adequate conditions are theoretically proven to guarantee that the trajectory of every solution for the chaotic neural networks passes through each impulsive surface only once. Second, by designing segmented controllers and aperiodic intermittent controllers, respectively, making use of the comparison principle and linear matrix inequality techniques, this paper establishes adequate conditions for the local exponential synchronization‐like control between impulsive chaotic neural networks. Finally, the validity of the proposed results was confirmed by using examples and numerical simulations.