Title :
A model for VLSI implementation of CNN image processing chips using current-mode techniques
Author :
Espejo, S. ; RodriguezVazquez, A. ; DominguezCastro, R. ; Linares, B. ; Huertas, J.L.
Author_Institution :
Dept. of Analog Circuit Design, Seville Univ., Spain
Abstract :
A new cellular neural network model is proposed. It allows simpler and faster VLSI implementation than previous models. Current-mode building blocks are presented for the design of CMOS image preprocessing chips (feature extraction, noise filtering, compound component detection, etc.) using the cellular neural network paradigm. Area evaluation for the new model shows a reduction of about 50% as compared to the use of current-mode techniques with conventional models. Experimental measurements of CMOS prototypes designed in a 1.6-μm n-well double-metal single-poly technology are reported
Keywords :
CMOS integrated circuits; VLSI; cellular neural nets; feature extraction; image processing equipment; image recognition; neural chips; 1.6 micron; CNN image processing chips; area evaluation; cellular neural network model; compound component detection; current-mode techniques; feature extraction; n-well double-metal single-poly technology; noise filtering; preprocessing chips; Analog circuits; Buildings; Cellular neural networks; Feature extraction; Filtering; Image processing; Integrated circuit modeling; Semiconductor device measurement; Semiconductor device modeling; Very large scale integration;
Conference_Titel :
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1281-3
DOI :
10.1109/ISCAS.1993.393885
