Global exponential synchronisation of a class of chaotic neural networks with distributed delays
by Xuyang Lou, Baotong Cui
International Journal of Modelling, Identification and Control (IJMIC), Vol. 3, No. 4, 2008

Abstract: This paper discusses the problem of exponential synchronisation for a class of chaotic neural networks which covers the Hopfield neural networks and cellular neural networks with distributed delays. Through the Lyapunov functional method and Hermitian matrices theory, a feedback control law is derived and its feedback gain matrix is designed to satisfy a certain Hamiltonian matrix without eigenvalues on the imaginary axis instead of directly solving an algebraic Riccati equation. Our results have been shown to be more extensive, less restrictive and easier to verify than those reported previously, which prepares the path for further research about synchronisation of delayed neural networks.

Online publication date: Mon, 29-Sep-2008

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 Modelling, Identification and Control (IJMIC):
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