DocumentCode
3254678
Title
Stability analysis of neural networks via Lyapunov approach
Author
Tanaka, Kazuo
Author_Institution
Dept. of Mech. Syst. Eng., Kanazawa Univ., Japan
Volume
6
fYear
1995
fDate
Nov/Dec 1995
Firstpage
3192
Abstract
This paper discusses stability of neural networks (NN) by Lyapunov approach. First, it is pointed out that the dynamic of NN systems can be represented by a class of nonlinear systems which is locally described by some different linear systems. Next, stability conditions for the class of nonlinear systems are derived and applied to stability analysis of NN systems. Finally, stability criteria of NN systems are demonstrated
Keywords
Lyapunov methods; circuit stability; neural nets; nonlinear systems; stability criteria; Lyapunov method; network dynamics; neural networks; nonlinear systems; stability analysis; stability criteria; Control systems; Fuzzy control; Learning systems; Mechanical systems; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Stability analysis; Stability criteria; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487296
Filename
487296
Link To Document