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• W2980525818 abstract "As an extension of single/multiple stability notion, Lagrange stability is considered here. A class of switched inertial neural networks (SINNs) is studied on both continuous-time and discrete-time domain. Two kinds of activation functions are evolved for the network. Through characteristic function approach, matrix measure strategy, and theory of time scales, Lagrange stability of delayed continuous-/discrete-time SINNs with lurie-type and bounded-type activation functions are addressed, respectively. The results also show that the criteria corresponding to discrete-time network approach to those corresponding to continuous-time one as the graininess function tends to zero. Two examples are given to show the effectiveness of the main results." @default.
• W2980525818 created "2019-10-25" @default.
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• W2980525818 date "2020-03-01" @default.
• W2980525818 modified "2023-09-30" @default.
• W2980525818 title "Lagrange stability of delayed switched inertial neural networks" @default.
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• W2980525818 doi "https://doi.org/10.1016/j.neucom.2019.10.052" @default.
• W2980525818 hasPublicationYear "2020" @default.
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