In this paper we show that the property of Global Asymptotic Stability is guaranteed for a class of neural circuits with a special form of nonsymmetric interconnection matrix. We also show that neural networks used to solve typical optimization problems (such as linear and quadratic programming problems) fall into the class of circuits here studied and are characterized by a unique globally asymptotically stable equilibrium.
Forti, M., Liberatore, A., Manetti, S., Marini, M. (1993). Global asymptotic stability for a class of nonsymmetric neural networks. In 1993 IEEE International Symposium on Circuits and Systems (pp.2580-2583). IEEE [10.1109/ISCAS.1993.394293].
Global asymptotic stability for a class of nonsymmetric neural networks
Forti M.;
1993-01-01
Abstract
In this paper we show that the property of Global Asymptotic Stability is guaranteed for a class of neural circuits with a special form of nonsymmetric interconnection matrix. We also show that neural networks used to solve typical optimization problems (such as linear and quadratic programming problems) fall into the class of circuits here studied and are characterized by a unique globally asymptotically stable equilibrium.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11365/30131
Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo