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/).
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 -