DocumentCode :
2427277
Title :
A partitioning scheme for optoelectronic neural networks
Author :
Wagner, T.D. ; Nash, D.A. ; Blair, J.R.S. ; Ressler, E.K. ; Shoop, B.L.
Author_Institution :
Dept. of Electr. Eng., US Mil. Acad., West Point, NY, USA
fYear :
2000
fDate :
24-28 July 2000
Abstract :
Smart pixel technology provides a promising technological alternative for the implementation of the error diffusion network (EDN) because optical input, electronic processing, and optical output are integrated in a single array. While current smart pixel technology could support 256/spl times/256 array sizes, it is of interest to investigate partitioning approaches which use smaller physical array sizes to achieve the same functionality and performance as larger arrays. One approach to this partitioning is to divide a large image into smaller sub-images, multiplex these sub-images into a small smart pixel EDN, and then demultiplex the partitions into the resulting full-sized image. This concept is demonstrated.
Keywords :
Hopfield neural nets; image processing; optical neural nets; smart pixels; Hopfield networks; digital halftoning; error diffusion network; optoelectronic neural networks; partitioning scheme; smart pixel technology; sub-images multiplexing; tiling; Application software; Digital images; Integrated optics; Military computing; Neural networks; Optical arrays; Optical network units; Photonics; Smart pixels; Tiles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronic-Enhanced Optics, Optical Sensing in Semiconductor Manufacturing, Electro-Optics in Space, Broadband Optical Networks, 2000. Digest of the LEOS Summer Topical Meetings
Conference_Location :
Aventura, FL, USA
ISSN :
1099-4742
Print_ISBN :
0-7803-6252-7
Type :
conf
DOI :
10.1109/LEOSST.2000.869703
Filename :
869703
Link To Document :
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