DocumentCode :
3494177
Title :
Analysis and Robust Design for Illusion CNNs
Author :
Li, Weidong ; Min, Lequan
Author_Institution :
Univ. of Sci. & Technol. Beijing, Beijing
fYear :
2008
fDate :
6-8 April 2008
Firstpage :
827
Lastpage :
831
Abstract :
The Cellular Neural Network (CNN), proposed by Chua et al in 1988, is a neural network with local connectivity. The CNN has been applied to the fields of image processing, pattern identification, biological visions and so on. The robust design is one of the important issues for the researches in CNN. This paper establishes the local rules of the Muller-Lyer Illusion (MLI) CNN introduced by Chua et. al. The robust design for the MLI CNN is given. A Ponzo Illusion (PI) CNN is introduced. The local rules and the theorem for the PI CNN are set up. Six numerical simulation examples are provided to illustrate the effectiveness of the methodology.
Keywords :
cellular neural nets; Muller-Lyer illusion cellular neural network; biological vision; image processing; local connectivity; pattern identification; robust design; Cellular neural networks; Design engineering; Displays; Hopfield neural networks; Image edge detection; Image processing; Mathematical model; Neural networks; Numerical simulation; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-1685-1
Electronic_ISBN :
978-1-4244-1686-8
Type :
conf
DOI :
10.1109/ICNSC.2008.4525330
Filename :
4525330
Link To Document :
بازگشت