Finite-time boundedness for uncertain discrete neural networks with time-delays and Markovian jumps
Date
2014
Authors
Zhang, Y.
Shi, P.
Nguang, S.
Zhang, J.
Karimi, H.
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Journal article
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Neurocomputing, 2014; 140:1-7
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Yingqi Zhang, Peng Shi, Sing Kiong Nguang, Jianhua Zhang, Hamid Reza Karimi
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Abstract
This paper is concerned with stochastic finite-time boundedness analysis for a class of uncertain discrete-time neural networks with Markovian jump parameters and time-delays. The concepts of stochastic finite-time stability and stochastic finite-time boundedness are first given for neural networks. Then, applying the Lyapunov approach and the linear matrix inequality technique, sufficient criteria on stochastic finite-time boundedness are provided for the class of nominal or uncertain discrete-time neural networks with Markovian jump parameters and time-delays. It is shown that the derived conditions are characterized in terms of the solution to these linear matrix inequalities. Finally, numerical examples are included to illustrate the validity of the presented results. © 2014 Elsevier B.V.
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© 2014 Elsevier B.V. All rights reserved.