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• W2002023533 abstract "Set-membership identification of Hammerstein-Wiener models is addressed in the paper. First, it is shown that computation of tight parameter bounds requires the solutions to a number of nonconvex constrained polynomial optimization problems where the number of decision variables increases with the length of the experimental data sequence. Then, a suitable convex relaxation procedure is presented to significantly reduce the computational burden of the identification problem. A detailed discussion of the identification algorithm properties is reported. Finally, a simulated example is used to show the effectiveness and the computational tractability of the proposed approach." @default.
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• W2002023533 date "2011-12-01" @default.
• W2002023533 modified "2023-10-02" @default.
• W2002023533 title "Set-membership identification of Hammerstein-Wiener systems" @default.
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• W2002023533 doi "https://doi.org/10.1109/cdc.2011.6161172" @default.
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