Finite-time synchronization of complex-valued neural networks with reaction-diffusion terms: an adaptive intermittent control approach

In this paper, we present a novel approach to achieve finite-time synchronization (FTS) in a certain class of fractional-order complex-valued neural networks (CVNNs) containing reaction-diffusion terms. The proposed method uses intermittent control and provides a theoretical analysis to establish criteria for achieving FTS. This is achieved through new Lyapunov functions based on the proposed system, deriving inequalities in the complex domain. To realize FTS, the study designs complex-valued intermittent controllers for the targeted CVNNs relying solely on the information obtained from the controlled nodes. Moreover, an adaptive controller is introduced to effectively regulate the control gain, and the FTS of CVNNs is analyzed. The effectiveness of the proposed control strategies and derived results is demonstrated by numerical examples.