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• W3043165038 endingPage "265" @default.
• W3043165038 startingPage "258" @default.
• W3043165038 abstract "This proposal considers the issue of L2-L∞ state estimation for delayed neural networks. A novel Lyapunov-Krasovskii functional is constructed, which contains augmented s-dependent integral and multiple integral terms. Then, in order to cooperate with the constructed Lyapunov-Krasovskii functional effectively to reduce the conservatism of the result, generalized free-weighting-matrix integral inequality and convex combination method are utilized. Meanwhile, multiple integral terms containing triple integral are utilized when analyzing the L2-L∞ performance. As a result, novel delay-dependent conditions are obtained, which can guarantee that the delayed neural network is asymptotically stable with desired performance level. Finally, the given numerical examples show the superiority of the proposed approach." @default.
• W3043165038 created "2020-07-23" @default.
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• W3043165038 date "2020-11-01" @default.
• W3043165038 modified "2023-10-18" @default.
• W3043165038 title "New optimal method for <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML altimg=si33.svg><mml:mrow><mml:msub><mml:mrow><mml:mi>L</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>-<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML altimg=si34.svg><mml:mrow><mml:msub><mml:mrow><mml:mi>L</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> state estimation of delayed neural networks" @default.
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• W3043165038 doi "https://doi.org/10.1016/j.neucom.2020.06.118" @default.
• W3043165038 hasPublicationYear "2020" @default.
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