Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Volume 26, Issue 10, Pages 2336-2345Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2014.2380451
Keywords
Impulsive systems; local impulsive effects; neural networks (NNs); stability analysis
Categories
Funding
- Natural Science Foundation through the Higher Education Institutions of Jiangsu Province, China [14KJB120014]
- Natural Science Foundation of Shanghai [13ZR1421300]
- Alexander von Humboldt Foundation of Germany
- National Natural Science Foundation of China [11426196, 61203235, 61304158, 61473189, 61375012]
- Hong Kong Polytechnic University, Hong Kong [G-YM53]
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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.
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