Programmable CNN based on optical thyristors for early image processing

Author

Buczynski, R. ; Thienpont, H. ; Jankowski, S. ; Szoplik, T. ; Veretennicoff, I.

Author_Institution

Lab. for Photonic Comput. & Perception, Vrije Univ., Brussels, Belgium

fYear

1998

fDate

14-17 Apr 1998

Firstpage

259

Lastpage

264

Abstract

An optoelectronic model of discrete time cellular neural networks (DTCNN) is presented. Connections between cells and parallel input-output are realized using optoelectronic devices. As an emitter-receiver device an optical thyristor is applied. Connections between cells are realized by diffractive Damman gratings. We propose a dual rail system for early processing of binary images. The CNN system performs mathematical morphology and space logic operations

Keywords

cellular neural nets; diffraction gratings; mathematical morphology; neural chips; optical neural nets; optoelectronic devices; photothyristors; binary images; diffractive Damman gratings; discrete time cellular neural networks; dual rail system; early image processing; emitter-receiver device; mathematical morphology; optical thyristors; optoelectronic model; programmable CNN; programmable cellular neural networks; space logic operations; Cellular neural networks; Diffraction gratings; Morphology; Optical computing; Optical devices; Optical diffraction; Optoelectronic devices; Rails; Stimulated emission; Thyristors;

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.1998.685382

Filename

685382