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• W2403879427 abstract "This paper investigates the problem of stability analysis for uncertain neutral-type neural networks with Markovian jumping parameters and interval time-varying delays. By separating the delay interval into multiple subintervals, a Lyapunov-Krasovskii methodology is established, which contains triple and quadruple integrals. The time-varying delay is considered to locate into any subintervals, which is different from existing delay-partitioning methods. Based on the proposed delay-partitioning approach, a stability criterion is derived to reduce the conservatism. Numerical examples show the effectiveness of the proposed methods. HighlightsNovel Lyapunov functions are constructed involving triple and quadruple integrals.The delay interval is decomposed into m equivalent subintervals.Newton-Leibniz formulas apply in each subinterval and derive weight-free matrices.A new inequality is used to reduce conservatism by reciprocally convex inequality." @default.
• W2403879427 created "2016-06-24" @default.
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• W2403879427 date "2016-09-01" @default.
• W2403879427 modified "2023-09-23" @default.
• W2403879427 title "Delay-partitioning approach design for stochastic stability analysis of uncertain neutral-type neural networks with Markovian jumping parameters" @default.
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• W2403879427 doi "https://doi.org/10.1016/j.neucom.2016.05.025" @default.
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