Asymptotically stable high-order neutral cellular neural networks with proportional delays and D operators

Chuangxia Huang, Renli Su, Jinde Cao and Songlin Xiao

Mathematics and Computers in Simulation (MATCOM), 2020, vol. 171, issue C, 127-135

Abstract: This paper aims to deal with the asymptotic stability of high-order neutral cellular neural networks (HNCNNs) incorporating proportional delays and D operators. Employing Lyapunov method, inequality technique and concise mathematical analysis proof, sufficient criteria on the global exponential asymptotical stability of the proposed HNCNNs are obtained. The main results provide us some light for designing stable HNCNNs and complement some earlier publications. In addition, simulations show that the theoretical convergence is in excellent agreement with the numerically observed behavior.

Keywords: Neutral cellular neural networks; Proportional delay; Asymptotic stability; D operator (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:171:y:2020:i:c:p:127-135

DOI: 10.1016/j.matcom.2019.06.001

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