Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/85022
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Type: Journal article
Title: Finite-time boundedness for uncertain discrete neural networks with time-delays and Markovian jumps
Author: Zhang, Y.
Shi, P.
Nguang, S.
Zhang, J.
Karimi, H.
Citation: Neurocomputing, 2014; 140:1-7
Publisher: Elsevier Science
Issue Date: 2014
ISSN: 0925-2312
1872-8286
Statement of
Responsibility: 
Yingqi Zhang, Peng Shi, Sing Kiong Nguang, Jianhua Zhang, Hamid Reza Karimi
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.
Keywords: Markovian jump systems; neural networks; discrete-time systems; stochastic finite-time boundedness; linear matrix inequalities
Rights: © 2014 Elsevier B.V. All rights reserved.
DOI: 10.1016/j.neucom.2013.12.054
Published version: http://dx.doi.org/10.1016/j.neucom.2013.12.054
Appears in Collections:Aurora harvest 7
Electrical and Electronic Engineering publications

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