A new current mode programmable cellular neural network

Author

Ravezzi, L. ; Betta, G. F Dalla ; Setti, G.

Author_Institution

Dipartimento di Ingegneria dei Mater., Trento Univ., Italy

fYear

1998

fDate

14-17 Apr 1998

Firstpage

253

Lastpage

258

Abstract

We report on the design of a full-analog current-mode CNN in a 1.2 μm CMOS technology, whose cell core is characterized by an intrinsic capability of weights control, low power consumption and small area occupation. Circuit simulations allowed the design approach to be validated and the electrical performance of the CNN to be predicted; moreover, it is shown that the proposed CNN can be successfully adopted for several applications in image processing. A preliminary CNN test-chip consisting of a 8×1 array for connected component detection and shadow detection, is currently being fabricated at IRST (Trento Italy) in a 2.5 μm CMOS technology

Keywords

CMOS analogue integrated circuits; analogue processing circuits; cellular neural nets; edge detection; neural chips; 1.2 μm CMOS technology; 1.2 mum; 2.5 μm CMOS technology; connected component detection; current mode programmable cellular neural network; full-analog current-mode CNN; image processing; shadow detection; CMOS technology; Cellular neural networks; Charge coupled devices; Circuit testing; Energy consumption; Hardware; Image processing; Lab-on-a-chip; Very large scale integration; Weight control;

fLanguage

English

Publisher

ieee

Conference_Titel

Cellular Neural Networks and Their Applications Proceedings, 1998 Fifth IEEE International Workshop on

Conference_Location

London

Print_ISBN

0-7803-4867-2

Type

conf

DOI

10.1109/CNNA.1998.685380

Filename

685380