Title
Stability criteria for stochastic neural networks with unstable subnetworks under mixed switchings
Abstract
In this paper, stability of a class of stochastic neural networks with switching signal is studied. Firstly, by means of the method of limiting average dwell time, we analyze the stability of switched systems which potentially contain unstable subsystems and stable subsystems simultaneously. Moreover, considering two types of switchings: stabilizing switchings and destabilizing switchings, we adopt time-dependent parameters to give a description of the relationship between two successive activated subsystems. Based on the obtained results for switched systems, some stability criteria for switched neural networks with stochastic disturbances are derived. At last, we present a numerical example to demonstrate the effectiveness of our results.
Year
DOI
Venue
2021
10.1016/j.neucom.2019.10.119
Neurocomputing
Keywords
DocType
Volume
Stochastic neural networks,Switching signal,Stability analysis,Limiting average dwell time
Journal
452
ISSN
Citations 
PageRank 
0925-2312
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Yaqi Wang1172.52
jungang lou218417.24
Hongyan Yan300.68
Jianquan Lu42337116.05