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}
}
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

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