Abstract
AbstractIn this article, without dividing a complex-valued neural network into two real-valued subsystems, the global synchronization of fractional-order complex-valued neural networks (FOCVNNs) is investigated by the Lyapunov direct method rather than the real decomposition method. It is worth mentioning that the partial adaptive control and partial linear feedback control schemes are introduced, by constructing suitable Lyapunov functions, some improved synchronization criteria are derived with the help of fractional differential inequalities and L’Hospital rule as well as some complex analysis techniques. Finally, simulation results are given to demonstrate the validity and feasibility of our theoretical analysis.
Funder
National Natural Science Foundation of China
Project Funded by China Postdoctoral Science Foundation
Natural Science Foundation of Xinjiang
Scientific Research Program of the Higher Education Institution of Xinjiang
Doctoral Scientific Research Foundation of Xinjiang University
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Algebra and Number Theory,Analysis
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