New H<sub>∞</sub> state estimation criteria of delayed static neural networks via the Lyapunov-Krasovskii functional with negative definite terms.
basic_science · Level V
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- Record sourced from PubMed, PMID 31887684.
- Also identified by DOI 10.1016/j.neunet.2019.12.008.
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Abstract
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<sub>∞</sub> 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.
Medical subject headings
- Neural Networks, Computer