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Quasi-Synchronization of Fractional Multiweighted Coupled Neural Networks Via Aperiodic Intermittent Control

IEEE transactions on cybernetics(2024)

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摘要
This article investigates the quasi-synchronization for fractional multiweighted coupled neural networks (FMCNNs) with discontinuous activation functions and mismatched parameters. First, under the generalized Caputo fractional-order derivative operator, a novel piecewise fractional differential inequality is established to study the convergence of fractional systems, which significantly extends some related published results. Subsequently, by exploiting the new inequality and Lyapunov stability theory, some sufficient quasi-synchronization conditions of FMCNNs are presented by aperiodic intermittent control. Meanwhile, the exponential convergence rate and synchronization error's bound are given explicitly. Finally, the validity of theoretical analysis is confirmed by numerical examples and simulations.
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关键词
Synchronization,Biological neural networks,Behavioral sciences,Fractional calculus,Convergence,Standards,Power system stability,Aperiodic intermittent control,discontinuous activation functions,fractional multiweighted neural networks,mismatched parameters,quasi-synchronization
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