Referenced Items are not available for this document.
The criteria for designing the basic building blocks of an analogically programmable cellular neural network (CNN) in a 1.5-μm CMOS technology are reported. The simulated electrical performances of a 10×10 CMOS CNN, consisting of about 8000 MOS transistors, are presented and discussed. It is shown that the designed CNN can be successfully used to perform such useful functions as noise removal, edge detection, hole filling, shadow detection, and connected component recognition
Published in:
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
(Volume:40
,
Issue:
3
)
Date of Publication: Mar 1993
- Page(s):
- 206 - 215
- ISSN :
- 1057-7130
- INSPEC Accession Number:
- 4477123
- Digital Object Identifier :
- 10.1109/82.222820
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Mar 1993
- Sponsored by :
- IEEE Circuits and Systems Society
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 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
