EconPapers    
Economics at your fingertips  
 

Delay-dependent attractor analysis of Hopfield neural networks with time-varying delays

Li Wan, Qinghua Zhou and Jie Liu

Chaos, Solitons & Fractals, 2017, vol. 101, issue C, 68-72

Abstract: This paper investigates the attractor of Hopfield neural networks with time-varying delays. By using Lyapunov–Krasovskii functional as well as linear matrix inequality, some novel delay-dependent sufficient conditions are derived to ensure the existence of pullback attractor of the considered networks. The constraint that the derivative function of the delay function is less than 1 is removed. Finally, two examples are given to demonstrate the effectiveness of our theoretical result.

Keywords: Hopfield neural networks; Time-varying delays; Pullback attractor (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077917301984
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:101:y:2017:i:c:p:68-72

DOI: 10.1016/j.chaos.2017.05.017

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().

 
Page updated 2025-03-19
Handle: RePEc:eee:chsofr:v:101:y:2017:i:c:p:68-72