State Estimation for Complex-Valued Inertial Neural Networks with Multiple Time Delays

Yaning Yu and Ziye Zhang
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Yaning Yu: College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China
Ziye Zhang: College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China

Mathematics, 2022, vol. 10, issue 10, 1-14

Abstract: In this paper, the problem of state estimation for complex-valued inertial neural networks with leakage, additive and distributed delays is considered. By means of the Lyapunov–Krasovskii functional method, the Jensen inequality, and the reciprocally convex approach, a delay-dependent criterion based on linear matrix inequalities (LMIs) is derived. At the same time, the network state is estimated by observing the output measurements to ensure the global asymptotic stability of the error system. Finally, two examples are given to verify the effectiveness of the proposed method.

Keywords: complex-valued inertial neural networks; state estimation; multiple time delays (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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