Recurrence and transience properties of some neural networks: An approach via fluid limit models

Recurrence and transience properties of some neural networks: An approach via fluid limit models

0.00 Avg rating0 Votes
Article ID: iaor20003206
Country: Netherlands
Volume: 32
Issue: 1/3
Start Page Number: 99
End Page Number: 130
Publication Date: Jan 1999
Journal: Queueing Systems
Authors: ,
Keywords: queues: theory, markov processes, networks: path
Abstract:

The subject of the paper is the stability analysis of some neural networks consisting of a finite number of interacting neurons. Following the approach of Dai we use the fluid limit model of the network to derive a sufficient condition for positive Harris-recurrence of the associated Markov process. This improves the main result in Karpelevich et al. and, at the same time, sheds some new light on it. We further derive two different conditions that are sufficient for transience of the state process and illustrate our results by classifying some examples according to positive recurrence or transience.

Reviews

Required fields are marked *. Your email address will not be published.