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

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

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 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.

Authors

  • Jing He
    School of Management, Guilin University of Aerospace Technology, Guilin, China.
  • Yan Liang
    Department of Chemistry and Biochemistry, The University of Arizona, Tucson, AZ, 85721, United States.
  • Feisheng Yang
    School of Automation, Northwestern Polytechnical University, Xi'an, PR China; Key Laboratory of Information Fusion Technology, Ministry of Education, Xi'an, PR China.
  • Feng Yang