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# Absolute stability conditions for discrete-time recurrent neural networks

@article{Jin1994AbsoluteSC, title={Absolute stability conditions for discrete-time recurrent neural networks}, author={Liang Jin and Peter N. Nikiforuk and Madan M. Gupta}, journal={IEEE transactions on neural networks}, year={1994}, volume={5 6}, pages={954-64} }

- Published 1994 in IEEE Trans. Neural Networks
DOI:10.1109/72.329693

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… CONTINUE READING