A current-mode cellular neural network implementation

Author

Varrientos, Joseph E. ; Sánchez-Sinencio, Edgar ; Ramirez-Angulo, Jaime

Author_Institution

Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA

Volume

40

Issue

3

fYear

1993

fDate

3/1/1993 12:00:00 AM

Firstpage

147

Lastpage

155

Abstract

A compact and efficient current-mode circuit implementation for a cellular neural network is presented. The implementation presented consists of current amplifiers, simple current mirrors, simple current sources, and transconductors. Experimental results from first-generation CMOS monolithic prototypes with fixed connection weights show the feasibility of the proposed implementation by successfully performing edge detection and noise removal image processing

Keywords

CMOS integrated circuits; constant current sources; edge detection; neural chips; current amplifiers; current mirrors; current sources; current-mode cellular neural network implementation; edge detection; first-generation CMOS monolithic prototypes; fixed connection weights; noise removal image processing; transconductors; Cellular neural networks; Circuit testing; Current mode circuits; Hardware; Image processing; Integrated circuit interconnections; Mirrors; Neural networks; Signal processing; Silicon;

fLanguage

English

Journal_Title

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

Publisher

ieee

ISSN

1057-7130

Type

jour

DOI

10.1109/82.222813

Filename

222813