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
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