Uniform Asymptotic Stability and Global Asymptotic Stability for Time-Delay Hopfield Neural Networks - Artificial Intelligence Applications and Innovations - Part I (AIAI 2012)
Conference Papers Year : 2012

Uniform Asymptotic Stability and Global Asymptotic Stability for Time-Delay Hopfield Neural Networks

Abstract

In this paper, we consider the uniform asymptotic stability and global asymptotic stability of the equilibrium point for time-delays Hopfield neural networks. Some new criteria of the system are derived by using the Lyapunov functional method and the linear matrix inequality approach for estimating the upper bound of the derivative of Lyapunov functional. Finally, we illustrate a numerical example showing the effectiveness of our theoretical results.
Fichier principal
Vignette du fichier
978-3-642-33409-2_50_Chapter.pdf (277.02 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01521395 , version 1 (11-05-2017)

Licence

Identifiers

Cite

Adnene Arbi, Chaouki Aouiti, Abderrahmane Touati. Uniform Asymptotic Stability and Global Asymptotic Stability for Time-Delay Hopfield Neural Networks. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. pp.483-492, ⟨10.1007/978-3-642-33409-2_50⟩. ⟨hal-01521395⟩
78 View
170 Download

Altmetric

Share

More