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Quasi-projective Synchronization for Caputo Type Fractional-order Complex-valued Neural Networks with Mixed Delays

Jingshun Cheng, Hai Zhang*, Weiwei Zhang, and Hongmei Zhang
International Journal of Control, Automation, and Systems, vol. 20, no. 5, pp.1723-1734, 2022

Abstract : Without decomposing the complex-valued systems into two real-valued subsystems, this paper investigates quasi-projective synchronization (QPS) problem for Caputo type fractional-order complex-valued neural networks (FOCVNNs) with mixed delays by choosing suitable controllers. To realize QPS, the linear feedback controller and adaptive feedback controller are designed, by constructing suitable Lyapunov function, utilizing the fractional Razumikhin theorem and the properties of Mittag-Leffler function and inequality technique, and several sufficient criteria for QPS of FOCVNNs with mixed delays are derived. In addition, the upper bound of the error of QPS is estimated. Finally, two numerical examples are simulated to verify the effectiveness and feasibility of the proposed results.

Keyword : Adaptive feedback control, fractional Razumikhin theorem, fractional-order complex-valued neural networks, linear feedback control, mixed delays, quasi-projection synchronization.

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