Bifurcations in Discrete-Time Delayed Hopfield Neural Networks of Two Neurons

Authors:
Eva Kaslik;Stefan Balint
Affiliations:
Department of Mathematics and Computer Science, West University of Timisoara, Romania;Department of Mathematics and Computer Science, West University of Timisoara, Romania
Venue:
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Year:
2008

Citing 6
Cited 0

Chaotic simulated annealing by a neural network model with transient chaos

Neural Networks
Chaos and asymptotical stability in discrete-time neural networks

Physica D
Associative dynamics in a chaotic neural network

Neural Networks
Elements of applied bifurcation theory (2nd ed.)

Elements of applied bifurcation theory (2nd ed.)
Dynamics of a class of discete-time neural networks and their comtinuous-time counterparts

Mathematics and Computers in Simulation
Stability and bifurcation analysis on a discrete-time neural network

Journal of Computational and Applied Mathematics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper is devoted to the bifurcation analysis of a two-dimensional discrete-time delayed Hopfield-type neural network. In the most general framework considered so far in the known literature, the stability domain of the null solution and the bifurcations occurring at its boundary are described in terms of two characteristic parameters. By applying the center manifold theorem and the normal form theory, the direction and stability of the existing bifurcations are analyzed.