By Topic

Analysis of Fault Tolerance of Cellular Neural Networks and Applications to Image Processing

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

3 Author(s)
Lidan Wang ; Chongqing Univ., Chongqing ; Xiaofan Yang ; Shukai Duan

This paper initiates the study of fault tolerant properties of faulty cellular neural networks (CNNs). A class of CNNs with single faulty cell is established, which is successfully applied to image processing: noise removing and image reversion. A series of computer simulations demonstrate CNNs have satisfied fault tolerant properties for image processing.

Published in:

Natural Computation, 2007. ICNC 2007. Third International Conference on  (Volume:3 )

Date of Conference:

24-27 Aug. 2007