Passivity analysis for neural networks of neutral type with Markovian jumping parameters and time delay in the leakage term. (English) Zbl 1219.92001
Summary: The problem of passivity analysis is investigated for neutral type neural networks with Markovian jumping parameters and time delay in the leakage term. The delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By constructing proper Lyapunov-Krasovskii functional, new delay-dependent passivity conditions are derived in terms of linear matrix inequalities (LMIs). Moreover, it is well known that the passivity behavior of neural networks is very sensitive to the time delay in the leakage term. Finally, three numerical examples are given to show the effectiveness and less conservatism of the proposed method.
MSC:
| 92B20 | Neural networks for/in biological studies, artificial life and related topics |
| 68T05 | Learning and adaptive systems in artificial intelligence |
| 60J20 | Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) |
| 15A45 | Miscellaneous inequalities involving matrices |
Keywords:
linear matrix inequality (LMI); delayed neural networks; passivity; interval time-varying delays; leakage delay; Lyapunov methodReferences:
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