Journal
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
Volume 357, Issue 15, Pages 10828-10843Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jfranklin.2020.08.017
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Funding
- National Natural Science Foundation of China [61403278, 61503280]
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This paper is concerned with the stability analysis of time-varying delay neural networks. By introducing some new delay integral terms and relaxation matrix, an augmented Lyapunov-Krasovskii functional (LKF) is constructed. In dealing with the inequality relations, a new method is proposed to deal with the integral term, which makes the inequality contain more neural network information and delay information. By solving the convergence of inequalities, the conservatism of the stability condition is improved and a more larger admissible maximum upper bounds (AMUBs) is obtained. Finally, some numerical examples are given to prove the effectiveness of the proposed method. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
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