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|Scopus||Web of Science®||Altmetric|
|Title:||New Stochastic robust stability criteria for time-varying delay neural networks with Markovian jump parameters|
|Citation:||Proceedings of the 27th Chinese Control Conference 2008, (CCC 2008), 2008, pp.634-637|
|Conference Name:||Chinese Control Conference (CCC) (16 Jul 2008 - 18 Jul 2008 : Kunming, Yunnan, China)|
|Qiu Jiqing, Shi Peng, Yang Hongjiu, Li Li, Li Jie|
|Abstract:||In this paper, the problem of stochastic robust stability of interval time-varying delay neural networks with Markovian jump parameters is investigated. The jumping parameters are modeled as a continuous-time, discrete-state Markov process. The linear factional uncertainty is considered, it means that a less conservative result will be obtained than using norm-bounded parameter uncertainties. And the derivative of the delay function can exceed one. Based on the lyapunov-krasovskii functional approach, a new delay-dependent stochastic stability criteria is presented in terms of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method.|
|Appears in Collections:||Aurora harvest 7|
Electrical and Electronic Engineering publications
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