The breaking of a delayed ring neural network contributes to stability: The rule and exceptions

Authors:
T. N. Khokhlova;M. M. Kipnis
Affiliations:
-;-
Venue:
Neural Networks
Year:
2013

Citing 2
Cited 0

Complex and chaotic dynamics in a discrete-time-delayed Hopfield neural network with ring architecture

Neural Networks
Dynamics of a discrete-time bidirectional ring of neurons with delay

IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks

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Abstract

We prove that in our mathematical model the breaking of a delayed ring neural network extends the stability region in the parameters space, if the number of the neurons is sufficiently large. If the number of neurons is small, then a ''paradoxical'' region exists in the parameters space, wherein the ring neural configuration is stable, while the linear one is unstable. We study the conditions under which the paradoxical region is nonempty. We discuss how our mathematical modeling reflects neurosurgical operations with the severing of particular connections in the brain.