Analysis on robust passivity of uncertain neural networks with time-varying delays via free-matrix-based integral inequality View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-07-20

AUTHORS

Shen-Ping Xiao, Hong-Hai Lian, Hong-Bing Zeng, Gang Chen, Wei-Hua Zheng

ABSTRACT

This paper investigates the robust delay-dependent passivity problem of neural networks (NNs) with time-varying delays and parameter uncertainties. A suitable augmented Lyapunov-Krasovskii functional (LKF) with triple integral term, which takes full use of the neuron activation function conditions and the information of time-delay in integral term, is constructed. Furthermore, by utilizing integral inequality proposed recently and the combining reciprocally convex method to estimate the derivative of the LKF, some less conservative robust passivity conditions are derived in terms of LMI. The superiority of presented approaches are demonstrated via two classic numerical examples. More... »

PAGES

2385-2394

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12555-016-0315-0

DOI

http://dx.doi.org/10.1007/s12555-016-0315-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1090832809


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