Sufficient condition for convergence of a relaxation algorithm in actual single-layer neural networks
Jacek M. Żurada, Wenwen Shen · IEEE Transactions on Neural Networks · 1990
Application of the contraction mapping theorem to single-layer feedback neural networks of a gradient-type is discussed. The sufficient condition for stability of a relaxation algorithm in actual continuous-time networks is derived and illustrated with an example. Results showing the stability of a numerical solution obtained with the relaxation algorithm are presented.