DocumentCode
3497113
Title
Robust Designs for Shadow Projection CNN
Author
Li, Weidong ; Min, Lequan
Author_Institution
Univ. of Sci. & Technol. Beijing, Beijing
fYear
2008
fDate
6-8 April 2008
Firstpage
1658
Lastpage
1662
Abstract
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.
Keywords
cellular neural nets; image processing; nonlinear systems; binary images; cellular neural network; cellular nonlinear network; image processing function; robust designs; shadow projection CNN; Application software; Biological system modeling; Biomedical signal processing; Cellular networks; Cellular neural networks; Image edge detection; Image processing; Numerical simulation; Robustness; Signal design;
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.2008.4525487
Filename
4525487
Link To Document