H∞ State Estimation for Stochastic Markovian Jumping Neural Network with Time-Varying Delay and Leakage Delay
| Autor: | Jing-Zhao Li, Ya-Jun Li, Zhao-Wen Huang |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Artificial neural network Applied Mathematics State estimator Attenuation 02 engineering and technology Computer Science Applications 020901 industrial engineering & automation Exponential stability Lyapunov functional Control and Systems Engineering Control theory Modeling and Simulation Norm (mathematics) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Stochastic neural network Markovian jumping Mathematics |
| Zdroj: | International Journal of Automation and Computing. 16:329-340 |
| ISSN: | 1751-8520 1476-8186 |
| Popis: | The H∞ state estimation problem for a class of stochastic neural networks with Markovian jumping parameters and leakage delay is investigated in this paper. By employing a suitable Lyapunov functional and inequality technic, the sufficient conditions for exponential stability as well as prescribed H∞ norm level of the state estimation error system are proposed and verified, and all obtained results are expressed in terms of strict linear matrix inequalities (LMIs). Examples and simulations are presented to show the effectiveness of the proposed methods, at the same time, the effect of leakage delay on stability of neural networks system and on the attenuation level of state estimator are discussed. |
| Databáze: | OpenAIRE |
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