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• W2040211176 abstract "This paper addresses global robust stability of a class of continuous-time interval neural networks that contain time-invariant uncertain parameters with their values being unknown but bounded in given compact sets. We first introduce the concept of diagonally constrained interval neural networks and present a necessary and sufficient condition for global exponential stability of these interval neural networks irregardless of any bounds of non-diagonal uncertain parameters in connection weight matrices. Then we extend the robust stability result to general interval neural networks by giving a sufficient condition. Simulation results illustrate the characteristics of the main results." @default.
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• W2040211176 date "2002-03-05" @default.
• W2040211176 modified "2023-10-16" @default.
• W2040211176 title "Global exponential stability of continuous-time interval neural networks" @default.
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• W2040211176 doi "https://doi.org/10.1103/physreve.65.036133" @default.
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