By Topic

Global robust stability of interval delayed neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
V. Singh ; Department of Electrical-Electronics Engineering, Atilim University, Ankara 06836, Turkey E-mail:

In recent years, the problem of global robust stability of Hopfield-type interval delayed neural networks has received considerable attention. A number of criteria for the global robust stability of such networks have been reported in the literature. On the basis of the idea of dividing (in respect of both the connection weight matrix A and the delayed connection weight matrix B) the given interval into two intervals, four new criteria for the global robust stability of such networks are established. The criteria are in the form of linear matrix inequality and, hence, computationally tractable. The criteria yield a less conservative condition compared with many recently reported criteria, as is demonstrated with an example.

Published in:

IET Control Theory & Applications  (Volume:3 ,  Issue: 6 )