DocumentCode
1721089
Title
Artificial neural networks in optical communications
Author
Frackerton, B. ; Giakos, G.C. ; Sobczyk, B. ; Formica, V. ; Patnekar, N.
Author_Institution
Dept. of Electr. Eng., Akron Univ., OH, USA
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
136
Lastpage
139
Abstract
In this paper, novel design principles aimed to improve the performance of optical receivers by means of neural networks, for enhanced signal-to-noise ratio, are presented. Paradigms from the area of optical communication networks, with emphasis, on optical wireless imaging angle-diversity receivers are presented, and discussed.
Keywords
diversity reception; neural nets; optical communication; optical receivers; angle-diversity receivers; artificial neural networks; optical communication networks; optical communications; optical receivers; optical wireless imaging; signal-to-noise ratio; Artificial neural networks; Biomedical optical imaging; Intelligent networks; Nonlinear optics; Optical computing; Optical fiber communication; Optical fiber networks; Optical receivers; Optical sensors; Optical signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Virtual and Intelligent Measurement Systems, 2002. VIMS '02. 2002 IEEE International Symposium on
Print_ISBN
0-7803-7344-8
Type
conf
DOI
10.1109/VIMS.2002.1009371
Filename
1009371
Link To Document