4.6 Article

Multiple Mittag-Leffler Stability of Fractional-Order Complex-Valued Memristive Neural Networks With Delays

Journal

IEEE TRANSACTIONS ON CYBERNETICS
Volume 53, Issue 9, Pages 5815-5825

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2022.3194059

Keywords

Biological neural networks; Stability criteria; Circuit stability; Delays; Behavioral sciences; Neurons; Artificial neural networks; Complex-valued neural networks (CVNNs); fractional-order; memristive neural networks; multiple Mittag-Leffler stability

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This article discusses the coexistence and dynamical behaviors of multiple equilibrium points in fractional-order complex-valued memristive neural networks with delays. The conditions for the existence of multiple equilibrium points are proposed, and the stability of these points is proven using the Lyapunov function. The effectiveness of the theoretical analysis is verified through computer simulations.
This article discusses the coexistence and dynamical behaviors of multiple equilibrium points (Eps) for fractional-order complex-valued memristive neural networks (FCVMNNs) with delays. First, based on the state space partition method, some sufficient conditions are proposed to guarantee that there are multiple Eps in one FCVMNN. Then, the Mittag-Leffler stability of those multiple Eps is proved by using the Lyapunov function. Simultaneously, the enlarged attraction basins are obtained to improve and extend the existing theoretical results in the previous literature. In addition, some existing stability results in the literature are special cases of a new result herein. Finally, two illustrative examples with computer simulations are presented to verify the effectiveness of theoretical analysis.

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