Distributed mode-dependent state estimation for semi-Markovian jumping neural networks via sampled data

Chao Ma, Wei Wu and Yinlin Li

International Journal of Systems Science, 2019, vol. 50, issue 1, 216-230

Abstract: In this paper, a novel distributed state estimation scheme with sampled data is proposed for the semi-Markovian jumping neural networks (SMJNNs) with time-varying delays. In particular, mode-dependent distributed state estimators are designed to provide more flexibility. Based on the mode-dependent Lyapunov-Krasovskii functional, sufficient criteria are presented for ensuring the existence of the state estimators, based on which the desired mode-dependent estimator gains are further obtained. Finally, an illustrative example is presented for verifying the effectiveness and applicability of our theoretical results.

Date: 2019
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DOI: 10.1080/00207721.2018.1552771

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