Abstract
The paper deals with a discrete-time recurrent neural network designed with dynamic neural models. Dynamics is reproduced within each single neuron, hence the considered network is a locally recurrent globally feed-forward. In the paper, conditions for global stability of the considered neural network are derived using the pole placement and Lyapunov second method. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Patan, K., Korbicz, J., & Prȩtki, P. (2005). Global stability conditions of locally recurrent neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3697 LNCS, pp. 191–196). https://doi.org/10.1007/11550907_31
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