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

Robust Designs for Shadow Projection CNN

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)
Weidong Li ; Univ. of Sci. & Technol. Beijing, Beijing ; Lequan Min

The cellular neural/nonlinear network (CNN) has become a useful tool for image and signal processing, biological visions, and higher brain functions. Based on our previous research, this paper gives local rules, and set up a series theorems of robust designs for shadow projection CNN in processing binary images, which provide parameter inequalities to determine parameter intervals for implementing the prescribed image processing function. Some numerical simulation examples are given.

Published in:

Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on

Date of Conference:

6-8 April 2008

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.