DocumentCode
2740941
Title
CMOL-Based Cellular Neural Networks and Parallel Processor for Future Image Processing
Author
Zhang, Wancheng ; Wu, Nan-Jian
Author_Institution
State Key Lab. for Superlattices & Microstructures, Chinese Acad. of Sci., Beijing
fYear
2008
fDate
18-21 Aug. 2008
Firstpage
737
Lastpage
740
Abstract
Hybrid CMOS/molecular (CMOL) circuits are promising for future high-performance VLSIs. Recently, digital and mixed-signal CMOL-based image-processing circuits were proposed. Although these circuits have ultra-high performances, several problems exist. In this paper, CMOL-based analog cellular neural network (CNN) and digital parallel image processor is proposed. The CMOL-based CNN has high speed and good fabrication tolerance. The parallel processor has high peak performance with easy configurability.
Keywords
CMOS integrated circuits; VLSI; cellular neural nets; hybrid integrated circuits; image processing; molecular electronics; nanoelectronics; parallel processing; CMOL-based cellular neural networks; CMOL-based image processing circuits; VLSI; digital parallel image processor; future image processing; hybrid CMOS/molecular circuits; parallel processor; CMOS memory circuits; CMOS process; CMOS technology; Cellular neural networks; Image processing; Laboratories; Pins; Semiconductor superlattices; Switches; Switching circuits;
fLanguage
English
Publisher
ieee
Conference_Titel
Nanotechnology, 2008. NANO '08. 8th IEEE Conference on
Conference_Location
Arlington, TX
Print_ISBN
978-1-4244-2103-9
Electronic_ISBN
978-1-4244-2104-6
Type
conf
DOI
10.1109/NANO.2008.221
Filename
4617203
Link To Document