Abstract
This paper is concerned with the sampled-data state estimation problem for neural networks of neutral-type with time-varying delays. A new state estimator was designed based on the sampled measurements. The sufficient condition for the existence of state estimator is derived by using the Lyapunov functional method. A numerical example is given to show the effectiveness of the proposed estimator.
This work was jointly supported by the National Natural Science Foundation of China under Grant 11226116, the Fundamental Research Funds for the Central Uni- versities JUSRP51317B.
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Xu, X., Yang, C., Hu, M., Yang, Y., Li, L. (2015). A New Sampled-Data State Estimator for Neural Networks of Neutral-Type with Time-Varying Delays. In: Hu, X., Xia, Y., Zhang, Y., Zhao, D. (eds) Advances in Neural Networks – ISNN 2015. ISNN 2015. Lecture Notes in Computer Science(), vol 9377. Springer, Cham. https://doi.org/10.1007/978-3-319-25393-0_14
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DOI: https://doi.org/10.1007/978-3-319-25393-0_14
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