Existence and stability of anti-periodic solutions for FCNNs with time-varying delays and impulsive effects on time scales
by Hongmei Bao
International Journal of Computing Science and Mathematics (IJCSM), Vol. 9, No. 5, 2018

Abstract: This paper deals with the existence and global exponential stability of anti-periodic solutions for fuzzy cellular neural networks (FCNNs) with time-varying delays and impulsive effects on time scales. Using the theory of coincidence degree, inequality technique and constructing some suitable Lyapunov functional, some sufficient conditions are obtained for the existence and global exponential stability of anti-periodic solutions for FCNNs with time-varying delays and impulsive effects on time scales. These results are less restrictive than those given in the earlier references. Moreover an example is provided to illustrate results obtained.

Online publication date: Mon, 08-Oct-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computing Science and Mathematics (IJCSM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com