Passivity analysis of neural networks with two different Markovian jumping parameters and mixed time delays |
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| Affiliation: | 1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China;2. Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1;3. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu611731, PR China |
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| Abstract: | This paper studies the problem of passivity analysis for neural networks with two different Markovian jumping parameters and mixed time delays utilizing some integral inequalities. The integral inequalities produce sharper bounds than what the Jensen's inequality produces, consequently, better results are obtained. The Markovian jumping parameters in connection weight matrices and discrete delay are assumed to be different in the system model. By constructing a new appropriate Lyapunov-Krasovskii functional (LKF), some sufficient conditions are established which guarantee the passivity of the proposed model. Numerical examples are given to show the less conservatism and effectiveness of the proposed method. |
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| Keywords: | Passivity analysis Markovian jumping parameters Leakage delay Neural networks |
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