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• W2615520810 abstract "This paper investigates the global dissipativity and globally exponential dissipativity for neural networks with both interval time-varying delays and interval distributed time-varying delays. By constructing a set of appropriated Lyapunov–Krasovskii functionals and employing Newton–Leibniz formulation and free weighting matrix method, some dissipativity criteria that are dependent on the upper and lower bounds of the time-varying delays are derived in terms of linear matrix inequalities (LMIs), which can be easily verified via the LMI toolbox. Moreover, a positive invariant and globally attractive set is derived via the established LMIs. Finally, two numerical examples and their simulations are provided to demonstrate the effectiveness of the proposed criteria." @default.
• W2615520810 created "2017-05-26" @default.
• W2615520810 creator A5034731039 @default.
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• W2615520810 date "2017-12-01" @default.
• W2615520810 modified "2023-10-18" @default.
• W2615520810 title "Delay-dependent dissipativity of neural networks with mixed non-differentiable interval delays" @default.
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• W2615520810 doi "https://doi.org/10.1016/j.neucom.2017.04.059" @default.
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