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Mittag–Leffler Synchronization of Delayed Fractional Memristor Neural Networks via Adaptive Control

Yonggui Kao, Ying Li, Ju H. Park, Xiangyong Chen

2020IEEE Transactions on Neural Networks and Learning Systems126 citationsDOI

Abstract

This brief is devoted to exploring the global Mittag-Leffler (ML) synchronization problem of fractional-order memristor neural networks (FOMNNs) with leakage delay via a hybrid adaptive controller. By applying Fillipov's theory and the Lyapunov functional method, the novel algebraic sufficient condition for the global ML synchronization of FOMNNs is derived. Finally, a simulation example is presented to show the practicability of our findings.

Topics & Concepts

MemristorSynchronization (alternating current)Control theory (sociology)Controller (irrigation)Artificial neural networkComputer scienceAdaptive controlFractional calculusMathematicsControl (management)Topology (electrical circuits)Applied mathematicsArtificial intelligenceElectronic engineeringEngineeringAgronomyBiologyCombinatoricsNeural Networks Stability and SynchronizationAdvanced Memory and Neural Computingstochastic dynamics and bifurcation
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