Analog CMOS implementation of cellular neural networks

Author

Baktir, Izzet Adil ; Tan, Mehmet Ali

Author_Institution

Dept. of Electr. & Electron. Eng., Bilkent Univ., Ankara, Turkey

Volume

40

Issue

3

fYear

1993

fDate

3/1/1993 12:00:00 AM

Firstpage

200

Lastpage

206

Abstract

The analog CMOS circuit realization of cellular neural networks with transconductance elements is presented. This realization can be easily adapted to various types of applications in image processing just by choosing the appropriate transconductance parameters according to the predetermined coefficients. The effectiveness of the designed circuits for connected component detection is shown by HSPICE simulations. For fixed function cellular neural network circuits, the number of transistors is reduced further by using multi-input transconductance elements

Keywords

CMOS integrated circuits; SPICE; analogue processing circuits; circuit analysis computing; neural chips; HSPICE simulations; analog CMOS circuit realization; cellular neural networks; connected component detection; multi-input transconductance elements; predetermined coefficients; transconductance elements; Artificial neural networks; Biological neural networks; CMOS analog integrated circuits; Cellular neural networks; Image processing; Parallel processing; Transconductance; Transducers; Very large scale integration; Voltage;

fLanguage

English

Journal_Title

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7130

Type

jour

DOI

10.1109/82.222819

Filename

222819