Title :
Stability criteria of discrete-time analog neural networks
Author :
Jin, Liang ; Gupta, Madan M. ; Nikiforuk, Peter N.
Author_Institution :
Intelligent Syst. Res. Lab., Saskatchewan Univ., Saskatoon, Sask., Canada
Abstract :
In this short paper, some globally asymptotical stability criteria for the equilibrium states of a class of discrete-time dynamic neural networks with continuous states and asymmetrical weight matrices are presented. The resulting stability criteria are represented by either the existence of the positive diagonal solutions of the Lyapunov equations or some inequalities. Finally, some examples are provided for demonstrating the global stability conditions presented
Keywords :
asymptotic stability; discrete time systems; neural nets; stability criteria; Lyapunov equations; asymmetrical weight matrices; continuous states; discrete-time analog neural networks; equilibrium states; global stability; globally asymptotical stability criteria; Educational institutions; Equations; Intelligent networks; Intelligent systems; Laboratories; Linear matrix inequalities; Lyapunov method; Neural networks; Stability criteria; Testing;
Conference_Titel :
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-2685-7
DOI :
10.1109/CDC.1995.478609
