Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/43609
Title: Stochastic stability of delayed neural networks with local impulsive effects
Authors: Zhang, W
Tang, Y
Wong, WK 
Miao, Q
Keywords: Impulsive systems
Local impulsive effects
Neural networks (NNs)
Stability analysis
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on neural networks and learning systems, 2015, v. 26, no. 10, 06998862, p. 2336-2345 How to cite?
Journal: IEEE transactions on neural networks and learning systems 
Abstract: In this paper, the stability problem is studied for a class of stochastic neural networks (NNs) with local impulsive effects. The impulsive effects considered can be not only nonidentical in different dimensions of the system state but also various at distinct impulsive instants. Hence, the impulses here can encompass several typical impulses in NNs. The aim of this paper is to derive stability criteria such that stochastic NNs with local impulsive effects are exponentially stable in mean square. By means of the mathematical induction method, several easy-to-check conditions are obtained to ensure the mean square stability of NNs. Three examples are given to show the effectiveness of the proposed stability criterion.
URI: http://hdl.handle.net/10397/43609
ISSN: 2162-237X (print)
2162-2388 (online)
DOI: 10.1109/TNNLS.2014.2380451
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