Journal
APPLIED MATHEMATICS AND COMPUTATION
Volume 294, Issue -, Pages 102-120Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2016.08.043
Keywords
Neural networks; Time-varying delay; Generalized free-weighting-matrix approach; Stability
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Funding
- National Natural Science Foundation of China [61503351, 51428702, 61304011]
- Hubei Provincial Natural Science Foundation of China [2015CFA010]
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This paper investigates the delay-dependent stability problem of continuous neural networks with a bounded time-varying delay via Lyapunov-Krasovskii functional (LKF) method. This paper focuses on reducing the conservatism of stability criteria by estimating the derivative of the LKF more accurately. Firstly, based on several zero-value equalities, a generalized free-weighting-matrix (GFWM) approach is developed for estimating the single integral term. It is also theoretically proved that the GFWM approach is less conservative than the existing methods commonly used for the same task. Then, the GFWM approach is applied to investigate the stability of delayed neural networks, and several stability criteria are derived. Finally, three numerical examples are given to verify the advantages of the proposed criteria. (C) 2016 Elsevier Inc. All rights reserved.
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