By Topic

New Delay-Dependent Stability Criteria for Neural Networks With Two Additive Time-Varying Delay Components

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
$31 $13
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

2 Author(s)
Hanyong Shao ; Sch. of Electr. & Inf. Autom., Qufu Normal Univ., Rizhao, China ; Qing-Long Han

This brief is concerned with delay-dependent stability for neural networks with two additive time-varying delay components. By constructing a new Lyapunov functional and using a convex polyhedron method to estimate the derivative of the Lyapunov functional, some new delay-dependent stability criteria are derived. These stability criteria are less conservative than some existing ones. An example is given to demonstrate the less conservatism of the stability results.

Published in:

Neural Networks, IEEE Transactions on  (Volume:22 ,  Issue: 5 )