DocumentCode
3254813
Title
Stability analysis techniques for competitive neural networks with different time-scales
Author
Meyer-Bäse, Anke ; Ohl, Frank ; Scheich, Henning
Author_Institution
Inst. for Digital Tech., Tech. Hochschule Darmstadt, Germany
Volume
6
fYear
1995
fDate
Nov/Dec 1995
Firstpage
3215
Abstract
We present new methods of analyzing the dynamics of a competitive neural system with different time scales: the K-monotone system theory developed by Kamke (1932) as a global analysis techniques, and the theory of singular perturbation as a local analysis method
Keywords
Hebbian learning; asymptotic stability; circuit stability; dynamics; neural nets; nonlinear systems; singularly perturbed systems; Hebbian learning; K-monotone system; asymptotic stability; competitive neural networks; dynamics; large scale systems; nonlinear systems; singular perturbation; stability analysis; time-scales; Equations; Hebbian theory; Jacobian matrices; Lyapunov method; Network topology; Neural networks; Neurons; Spatiotemporal phenomena; Stability analysis; State-space methods;
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.1995.487300
Filename
487300
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