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• W3195553647 abstract "This paper studies the stability of delayed neural networks (DNNs). An extended version of reciprocally convex inequality named exponential type reciprocally convex inequality (ETRCI) is proposed, which covers some existing results as its special cases. By constructing some intermediary fractional-order polynomials, a set of novel functions named fractional order-polynomial-based functions (FOPFs) are proposed. From the structure of FOPFs, the relationship among system states and time-varying delay can be fully coupled without higher order time delays and zero components. Two merits are first contained in FOPFs compared with the related functions, i) the nonintegral, single, double, and triple integral terms are all introduced in augmentation forms and ii) the delay-product-type integral quadratic terms are constructed. Based on ETRCI and FOPFs, a new stability criterion is obtained for DNNs, in which the potential capacities of advanced bounding techniques are adequately explored and the system information is sufficiently captured. An example is illustrated to demonstrate the effectiveness of the obtained results." @default.
• W3195553647 created "2021-08-30" @default.
• W3195553647 creator A5032348000 @default.
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• W3195553647 date "2021-11-01" @default.
• W3195553647 modified "2023-10-02" @default.
• W3195553647 title "Stability analysis for delayed neural networks: A fractional-order function method" @default.
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• W3195553647 doi "https://doi.org/10.1016/j.neucom.2021.08.077" @default.
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