Fixed point analysis for discrete-time recurrent neural networks
L.K. Li · 2003
The author shows the existence of a fixed point for every recurrent neural network and uses a geometric approach to locate where the fixed points are. The stability is discussed for low-gain and high-gain situations. A generalized Hopfield saturation theorem is presented in a high gain situation for a discrete-time model version.>