Switched exponential state estimation and robust stability for interval neural networks with discrete and distributed time delays. (English) Zbl 1246.93088

Xu, Hongwen; Wu, Huaiqin; Li, Ning

Abstr. Appl. Anal. 2012, Article ID 103542, 20 p. (2012).

Summary: The interval exponential state estimation and robust exponential stability for the switched interval neural networks with discrete and distributed time delays are considered. Firstly, by combining the theories of the switched systems and the interval neural networks, the mathematical model of the switched interval neural networks with discrete and distributed time delays and the interval estimation error system are established. Secondly, by applying the augmented Lyapunov-Krasovskii functional approach and available output measurements, the dynamics of estimation error system is proved to be globally exponentially stable for all admissible time delays. Both the existence conditions and the explicit characterization of desired estimator are derived in terms of linear matrix inequalities (LMIs). Moreover, a delay-dependent criterion is also developed, which guarantees the robust exponential stability of the switched interval neural networks with discrete and distributed time delays. Finally, two numerical examples are provided to illustrate the validity of the theoretical results.

MSC:

93D09	Robust stability
93E10	Estimation and detection in stochastic control theory
92B20	Neural networks for/in biological studies, artificial life and related topics

Keywords:

exponential state estimation; robust stability

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