Title :
Stability analysis of neural networks via Lyapunov approach
Author_Institution :
Dept. of Mech. Syst. Eng., Kanazawa Univ., Japan
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;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.487296
