Projective Synchronization of Non-Autonomous Neural Networks with Caputo Derivatives and Mixed Delays

This paper investigates the projective synchronization problem for a class of non-autonomous neural networks with Caputo fractional derivatives and mixed delays. First, by simultaneously introducing discrete and distributed delays into the model, the drive and response systems and the corresponding error system are constructed, and a synchronization controller is designed. Second, by constructing an appropriate quadratic Lyapunov function and estimating the nonlinear and mixed-delay terms in a unified manner, a fractional Halanay-type delay inequality is derived. Based on this inequality, sufficient conditions are obtained to guarantee global asymptotic projective synchronization for this class of neural networks. Finally, numerical simulations are presented to verify the theoretical results and the numerical consistency of the adopted discretization scheme.