International Journal of Computational Intelligence Systems

Volume 8, Issue 2, April 2015, Pages 381 - 394

Dynamics of High-order Fuzzy Cellular Neural Networks with Time-varying Delays

Authors
Manchun Tan, Shuping Xu, Zhong Li
Corresponding Author
Manchun Tan
Received 30 April 2014, Accepted 21 December 2014, Available Online 1 April 2015.
DOI
10.1080/18756891.2015.1017368How to use a DOI?
Keywords
High-order neural networks, Equilibrium point, Boundedness, Time-varying delays, Exponential stability
Abstract

In this paper, dynamic behavior of a class of high-order fuzzy cellular neural networks (HFCNNs) with time-varying delays is investigated. Compared with the previous results in the literature, the restrictions are loosed, since we do not assume the boundedness and monotonicity on the activation functions, and the differentiability of time-varying delay functions. Some sufficient conditions are derived for ascertaining the existence, uniqueness and exponential stability of equilibrium point and uniform boundedness of solutions of the HFCNNs. Finally, two examples are given to show the effectiveness of the proposed criteria, which complement some previously known results.

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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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
8 - 2
Pages
381 - 394
Publication Date
2015/04/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2015.1017368How 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  - JOUR
AU  - Manchun Tan
AU  - Shuping Xu
AU  - Zhong Li
PY  - 2015
DA  - 2015/04/01
TI  - Dynamics of High-order Fuzzy Cellular Neural Networks with Time-varying Delays
JO  - International Journal of Computational Intelligence Systems
SP  - 381
EP  - 394
VL  - 8
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2015.1017368
DO  - 10.1080/18756891.2015.1017368
ID  - Tan2015
ER  -