4.7 Article

New H∞ state estimation criteria of delayed static neural networks via the Lyapunov-Krasovskii functional with negative definite terms

Journal

NEURAL NETWORKS
Volume 123, Issue -, Pages 236-247

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2019.12.008

Keywords

Static neural networks; H-infinity state estimation; Time-varying delay; Lyapunov-Krasovskii functional

Funding

  1. National Natural Science Foundation of China [61771399, 61873205]
  2. Shaanxi Natural Fund [2018MJ6048]

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In the estimation problem for delayed static neural networks (SNNs), constructing a proper Lyapunov-Krasovskii functional (LKF) is crucial for deriving less conservative estimation criteria. In this paper, a delay-product-type LKF with negative definite terms is proposed. Based on the third-order Bessel-Legendre (B-L) integral inequality and mixed convex combination approaches, a less conservative estimator design criterion is derived. Furthermore, the desired estimator gain matrices and the H-infinity performance index are obtained by solving a set of linear matrix inequalities (LMIs). Finally, a numerical example is given to demonstrate the effectiveness of the proposed method. (C) 2019 Elsevier Ltd. All rights reserved.

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