Stability analysis for discrete delayed Markovian jumping neural networks with partly unknown transition probabilities

Authors:
Y. Lu;W. Ren;S. Yi;Y. Zuo
Affiliations:
College of Information Technology, Heilongjiang Bayi Agricultural University, Daqing 163319, China and College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163 ...;College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China;College of Information Technology, Heilongjiang Bayi Agricultural University, Daqing 163319, China;College of Information Technology, Heilongjiang Bayi Agricultural University, Daqing 163319, China
Venue:
Neurocomputing
Year:
2011

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Abstract

This paper addresses the analysis problem of asymptotic stability for a class of uncertain neural networks with Markovian jumping parameters and time delays. The considered transition probabilities are assumed to be partially unknown. The parameter uncertainties are considered to be norm-bounded. A sufficient condition for the stability of the addressed neural networks is derived, which is expressed in terms of a set of linear matrix inequalities. A numerical example is given to verify the effectiveness of the developed results.