Dissipativity analysis of memristive neural networks with time-varying delays and randomly occurring uncertainties

Dissipativity theory is a very important concept in the field of control system. In this paper, we pay attention to the problem of dissipativity analysis of memristive neural networks with time‐varying delay and randomly occurring uncertainties(ROUs). Under the framework of Filippov solution, differ...

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Bibliographic Details
Published in:Mathematical methods in the applied sciences 2016-07, Vol.39 (11), p.2896-2915
Main Authors: Li, Ruoxia, Cao, Jinde
Format: Article
Language:English
Subjects:
Control systems
Criteria
Delay
Dissipation
dissipativity
Inequalities
linear matrix inequalities (LMIs)
Mathematical models
memristive
Neural networks
randomly occurring uncertainties (ROUs)
time-varying delays
Uncertainty
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Summary:Dissipativity theory is a very important concept in the field of control system. In this paper, we pay attention to the problem of dissipativity analysis of memristive neural networks with time‐varying delay and randomly occurring uncertainties(ROUs). Under the framework of Filippov solution, differential inclusion theory, by employing a proper Lyapunov functional, and some inequality techniques, the dissipativity criteria are obtained in terms of LMIs. It should be noteworthy that the uncertainty terms as well as the ROUs are separately taken into consideration, in which the uncertainties are norm‐bounded and the ROUs obey certain mutually uncorrelated Bernoulli‐distributed white noise sequences. Finally, the effectiveness of the proposed method will be verified via numerical example. Copyright © 2015 John Wiley & Sons, Ltd.
ISSN:0170-4214
1099-1476
DOI:10.1002/mma.3738