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• W2147347068 abstract "A framework and stability conditions are presented for the analysis of stability of three different classes of dynamic artificial neural networks: (1) neural state space models, (2) global input-output models, and (3) dynamic recurrent neural networks. The models are transformed into a standard nonlinear operator form for which linear matrix inequality-based stability analysis is applied. Theory and numerical examples are used to draw connections and make comparisons to stability conditions reported in the literature for dynamic artificial neural networks." @default.
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• W2147347068 date "2011-09-01" @default.
• W2147347068 modified "2023-09-28" @default.
• W2147347068 title "Standard representation and stability analysis of dynamic artificial neural networks: A unified approach" @default.
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• W2147347068 doi "https://doi.org/10.1109/cacsd.2011.6044536" @default.
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