Global attracting set for a class of delayed Hopfield neural networks

DOI

10.2991/fmsmt-17.2017.238How to use a DOI?

Keywords

Hopfield neural networks; Global attracting set; Integral inequality.

Abstract

The asymptotic behaviors of a class of delayed Hopfield neural networks are investigated. By applying the property of nonnegative matrix and an integral inequality, some novel sufficient conditions are derived to ensure the existence of the global attracting set and the stability in a Lagrange sense for the considered networks. Finally, a numerical example is given to demonstrate the effectiveness of our theoretical result. Our criteria are easily tested by Matlab LMI Toolbox.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qinghua Zhou
AU  - Li Wan
PY  - 2017/04
DA  - 2017/04
TI  - Global attracting set for a class of delayed Hopfield neural networks
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 1217
EP  - 1221
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.238
DO  - 10.2991/fmsmt-17.2017.238
ID  - Zhou2017/04
ER  -