Title
What Connection Topology Prohibit Chaos in Continuous Time Networks?
Abstract
In this paper, we are concerned with two interesting problems in the dynamics of neural networks. What connection topology will prohibit chaotic behavior in a continuous time neural network (NN). To what extent is a continuous time neural network (NN) described by continuous ordinary differential equations simple enough yet still able to exhibit chaos? We study these problems in the context of the classical neural networks with three neurons, which can be described by three-dimensional autonomous ordinary differential equations. We first consider the case where there is no direct interconnection between the first neuron and the third neuron. We then discuss the case where each pair of neurons has a direct connection. We show that the existence of the directed loop in connection topology is necessary for chaos to occur.
Year
DOI
Venue
2007
10.1142/S021952590700129X
ADVANCES IN COMPLEX SYSTEMS
Keywords
Field
DocType
chaos,connection topology,continuous time neural network
Topology,Ordinary differential equation,Artificial neural network,Chaotic,Interconnection,Mathematics
Journal
Volume
Issue
ISSN
10
4
0219-5259
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Xiaosong Yang137852.10
Quan Yuan286.54
Lin Wang367676.90