Cart (Loading....) | Create Account
Close category search window
 

A new delayed projection neural network for solving quadratic programming problems

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

4 Author(s)
Bonan Huang ; Sch. of Inf. Sci. & Eng., Northeastern Univ., Shengyang, China ; Huaguang Zhang ; Zhanshan Wang ; Meng Dong

In this paper, a new delayed projection neural network with mixed delays is proposed for solving a class of quadratic programming (QP) problems. By the Lyapunov-Krasovskii theory and the linear matrix inequality (LMI) method, the proposed neural network is proved to be convergent to the optimal solution of the QP problems exponentially. The validity of the proposed neural network is verified by two simulation examples.

Published in:

Neural Networks (IJCNN), The 2010 International Joint Conference on

Date of Conference:

18-23 July 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.