Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)

Global attracting set for a class of delayed Hopfield neural networks

Authors
Qinghua Zhou, Li Wan
Corresponding Author
Qinghua Zhou
Available Online April 2017.
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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Volume Title
Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
10.2991/fmsmt-17.2017.238
ISSN
2352-5401
DOI
10.2991/fmsmt-17.2017.238How to use a DOI?
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/).

Cite this article

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  -