Quasi-projective synchronization of fractional-order complex-valued recurrent neural networks

Neural Networks : the Official Journal of the International Neural Network Society
Shuai YangHaijun Jiang

Abstract

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.

Citations

Jan 10, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Shuai YangHaijun Jiang
Dec 1, 2019·Neural Networks : the Official Journal of the International Neural Network Society·Xingxing YouZhenjiang Zhao
Dec 31, 2019·Neural Networks : the Official Journal of the International Neural Network Society·Xingxing YouZhenjiang Zhao
Jan 27, 2020·Neural Networks : the Official Journal of the International Neural Network Society·Juan YuLeimin Wang

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