Quasi-projective synchronization of fractional-order complex-valued recurrent neural networks.
In this paper, without separating the complex-valued neural networks into two real-valued systems, the quasi-projective synchronization of fractional-order complex-valued neural networks is investigated. First, two new fractional-order inequalities are established by using the theory of complex functions, Laplace transform and Mittag-Leffler functions, which generalize traditional inequalities with the first-order derivative in the real domain. Additionally, different from hybrid control schemes given in the previous work concerning the projective synchronization, a simple and linear control strategy is designed in this paper and several criteria are derived to ensure quasi-projective synchronization of the complex-valued neural networks with fractional-order based on the established fractional-order inequalities and the theory of complex functions. Moreover, the error bounds of quasi-projective synchronization are estimated. Especially, some conditions are also presented for the Mittag-Leffler synchronization of the addressed neural networks. Finally, some numerical examples with simulations are provided to show the effectiveness of the derived theoretical results.
['Yang|Shuai|S|', 'Yu|Juan|J|', 'Hu|Cheng|C|', 'Jiang|Haijun|H|']
D005246:Feedback D016571:Neural Networks, Computer
Quasi-projective synchronization Complex-valued neural network Fractional-order derivative Linear feedback control