Title :
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
fDate :
3/1/1993 12:00:00 AM
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;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
