DocumentCode
303078
Title
New Lyapunov methodology: asymptotic stability of Hopfield neural networks
Author
Grujic, Ljuborrmir
Author_Institution
Ecole Nat. de Ingenieurs, Belfort, France
Volume
1
fYear
1996
fDate
17-20 Jun 1996
Firstpage
127
Abstract
The paper develops a new Lyapunov methodology for Hopfield neural networks (HNN). It determines an algorithm for an exact construction of a Lyapunov function v(.) for given HNN, which is based on a complete set of the necessary and sufficient conditions for (global) asymptotic stability of the isolated equilibrium state x=0
Keywords
Hopfield neural nets; Lyapunov methods; asymptotic stability; nonlinear systems; Hopfield neural networks; Lyapunov function; Lyapunov methodology; algorithm; asymptotic stability; global stability; isolated equilibrium state; Asymptotic stability; Equations; Hopfield neural networks; Inductors; Linear systems; Lyapunov method; Neural networks; Nonlinear systems; Sufficient conditions; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, 1996. ISIE '96., Proceedings of the IEEE International Symposium on
Conference_Location
Warsaw
Print_ISBN
0-7803-3334-9
Type
conf
DOI
10.1109/ISIE.1996.548404
Filename
548404
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