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• W2537112722 abstract "This paper first investigates the absolute exponential stability (AEST) of delayed neural networks with a general class of partially Lipschitz continuous and monotone increasing activation functions. The main results obtained are that if the interconnection matrix T of the delayed neural networks satisfies that -T is an H -matrix with nonnegative diagonal elements and there exists k satisfying the condition concerned, then the neural network system is absolutely stable (ABST)." @default.
• W2537112722 created "2016-10-28" @default.
• W2537112722 creator A5019248683 @default.
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• W2537112722 date "2003-08-27" @default.
• W2537112722 modified "2023-09-27" @default.
• W2537112722 title "On absolute stability of delayed neural networks" @default.
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• W2537112722 doi "https://doi.org/10.1109/icccas.2002.1179099" @default.
• W2537112722 hasPublicationYear "2003" @default.
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