New stability results for delayed neural networks with data packet dropouts

Xiao Cai, Shouming Zhong, Jun Wang and Kaibo Shi

Physica A: Statistical Mechanics and its Applications, 2020, vol. 555, issue C

Abstract: This paper further investigates the stability analysis of delayed neural networks (DNNs) with data packet dropouts. Firstly, the delay-product-type function method is introduced to construct a suitable Lyapunov–Krasovskii functional (LKF) with delay-dependent matrices, which fully considers the integral terms, non-integral terms and time-delay correlation terms. Then, by applying free-matrix-base inequality (FMBI) and other valid inequalities mathematical analysis techniques, new stability criteria are established. Meanwhile, by solving a set of linear matrix inequalities (LMIs), the corresponding controllers are designed to ensure the system state stabilization. Finally, two examples are given to demonstrate the validity and feasibility of the proposed method.

Keywords: Neural networks; Data packet dropouts; Time-varying delay; Integral inequality (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:555:y:2020:i:c:s0378437120303630

DOI: 10.1016/j.physa.2020.124727

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