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• W2116733726 abstract "An analysis of the absolute stability for a general class of discrete-time recurrent neural networks (RNN's) is presented. A discrete-time model of RNN's is represented by a set of nonlinear difference equations. Some sufficient conditions for the absolute stability are derived using Ostrowski's theorem and the similarity transformation approach. For a given RNN model, these conditions are determined by the synaptic weight matrix of the network. The results reported in this paper need fewer constraints on the weight matrix and the model than in previously published studies." @default.
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• W2116733726 date "1994-01-01" @default.
• W2116733726 modified "2023-09-27" @default.
• W2116733726 title "Absolute stability conditions for discrete-time recurrent neural networks" @default.
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• W2116733726 doi "https://doi.org/10.1109/72.329693" @default.
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