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
fDate :
6/24/1905 12:00:00 AM
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;
Conference_Titel :
Virtual and Intelligent Measurement Systems, 2002. VIMS '02. 2002 IEEE International Symposium on
Print_ISBN :
0-7803-7344-8
DOI :
10.1109/VIMS.2002.1009371
