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• W1991456514 abstract "This paper presents new results on neurodynamic optimization approaches to robust pole assignment based on four alternative robustness measures. One or two recurrent neural networks are utilized to optimize these measures while making exact pole assignment. Compared with existing approaches, the present neurodynamic approaches can result in optimal robustness in most cases with one of the robustness measures. Simulation results of the proposed approaches for many benchmark problems are reported to demonstrate their performances." @default.
• W1991456514 created "2016-06-24" @default.
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• W1991456514 date "2013-08-01" @default.
• W1991456514 modified "2023-09-22" @default.
• W1991456514 title "Neurodynamic optimization approaches to robust pole assignment based on alternative robustness measures" @default.
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• W1991456514 doi "https://doi.org/10.1109/ijcnn.2013.6706834" @default.
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