DocumentCode
1643684
Title
Design of a CMOS analog programmable cellular neural network
Author
Betta, G. F Dalla ; Graffi, S. ; Masetti, G. ; Kovács, Zs M.
Author_Institution
DEIS, Bologna Univ., Italy
fYear
1992
Firstpage
151
Lastpage
156
Abstract
The design of an analog programmable CNN architecture with low-power dissipation in a 1.5-μm CMOS technology is presented. After discussing the design of basic building blocks, the electrical performance of a 10×10 CMOS CNN, consisting of about 8000 MOS transistors, fully simulated at the device level, which can be analog-programmed by varying an external control voltage is discussed. The CNN can perform such functions as noise removal, hole filter, shadow detector, connected component recognition, and edge detector. The power consumption of the circuit is about 60 mW, which is about 1/3 of the power consumption of a previously reported nonprogrammable circuit
Keywords
CMOS integrated circuits; analogue processing circuits; image processing equipment; image recognition; neural chips; 1.5 micron; CMOS IC; MOS transistors; analog programmable cellular neural network; connected component recognition; design; edge detector; hole filter; neural chips; noise removal; shadow detector; CMOS process; CMOS technology; Cellular neural networks; Circuit simulation; Detectors; Energy consumption; Image edge detection; Mirrors; Neural networks; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and their Applications, 1992. CNNA-92 Proceedings., Second International Workshop on
Conference_Location
Munich
Print_ISBN
0-7803-0875-1
Type
conf
DOI
10.1109/CNNA.1992.274339
Filename
274339
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