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- W86565843 abstract "A novel H <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>∞</inf> design methodology for a neural network-based nonlinear filtering scheme is addressed. Firstly, neural networks are employed to approximate the nonlinearities. Next, the nonlinear dynamic system is represented by the mode-dependent linear difference inclusion (LDI). Finally, based on the LDI model, a neural network-based nonlinear filter (NNBNF) is developed to minimize the upper bound of H <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>∞</inf> gain index of the estimation error under some linear matrix inequality (LMI) constraints. Compared with the existing nonlinear filters, NNBNF is time-invariant and numerically tractable. The validity and applicability of the proposed approach are successfully demonstrated in an illustrative example." @default.
- W86565843 created "2016-06-24" @default.
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- W86565843 date "2008-02-01" @default.
- W86565843 modified "2023-09-23" @default.
- W86565843 title "Neural network-based H<inf>∞</inf> filtering for nonlinear systems with time-delays" @default.
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- W86565843 doi "https://doi.org/10.1016/s1004-4132(08)60059-6" @default.
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