Multiple-input transconductance CMOS amplifier for implementation in continously programmable cellular neural networks

Author

Kacprzak, Tomasz

Author_Institution

Inst. of Electron., Tech. Univ. Lodz

Volume

3

fYear

1998

fDate

1998

Firstpage

305

Abstract

In the paper a concept of reprogrammable Cellular Neural Network realized with multiple-input transconductance amplifiers is presented. A methodology of the circuit design is given, based on the CMOS VLSI technology. This approach is especially attractive for realization of CNNs for real-time image processing since it enables controlling the system templates parameters required during the processing task. The theoretical considerations are illustrated by computer simulation of connected component detector and by measurements of the characteristics of manufactured amplifier

Keywords

CMOS analogue integrated circuits; SPICE; VLSI; cellular neural nets; circuit simulation; digital simulation; image processing; neural net architecture; CMOS VLSI; CMOS amplifier; CNN; characteristics; circuit design; computer simulation; connected component detector; continously programmable cellular neural networks; multiple-input transconductance amplifiers; real-time image processing; CMOS technology; Cellular neural networks; Circuit synthesis; Computer simulation; Control systems; Detectors; Image processing; Real time systems; Transconductance; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Circuits and Systems, 1998 IEEE International Conference on

Conference_Location

Lisboa

Print_ISBN

0-7803-5008-1

Type

conf

DOI

10.1109/ICECS.1998.813996

Filename

813996