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Global Dissipativity and Quasi-Mittag–Leffler Synchronization of Fractional-Order Discontinuous Complex-Valued Neural Networks

Zhixia Ding, Hao Zhang, Zhigang Zeng, Le Yang, Sai Li

2021IEEE Transactions on Neural Networks and Learning Systems22 citationsDOI

Abstract

This article is concerned with fractional-order discontinuous complex-valued neural networks (FODCNNs). Based on a new fractional-order inequality, such system is analyzed as a compact entirety without any decomposition in the complex domain which is different from a common method in almost all literature. First, the existence of global Filippov solution is given in the complex domain on the basis of the theories of vector norm and fractional calculus. Successively, by virtue of the nonsmooth analysis and differential inclusion theory, some sufficient conditions are developed to guarantee the global dissipativity and quasi-Mittag-Leffler synchronization of FODCNNs. Furthermore, the error bounds of quasi-Mittag-Leffler synchronization are estimated without reference to the initial values. Especially, our results include some existing integer-order and fractional-order ones as special cases. Finally, numerical examples are given to show the effectiveness of the obtained theories.

Topics & Concepts

Differential inclusionSynchronization (alternating current)Artificial neural networkMathematicsNorm (philosophy)Control theory (sociology)Domain (mathematical analysis)Computer scienceBasis (linear algebra)Compact spaceApplied mathematicsChenDifferential (mechanical device)Frequency domainComplex networkDecompositionAlgorithmTime domainComplex systemComputer simulationNeural Networks Stability and SynchronizationNeural Networks and ApplicationsControl and Stability of Dynamical Systems
Global Dissipativity and Quasi-Mittag–Leffler Synchronization of Fractional-Order Discontinuous Complex-Valued Neural Networks | Litcius