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Proceedings Paper

Fiber optic Adaline neural networks
Author(s): Anjan K. Ghosh; Jim Trepka; Palacharla Paparao
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Paper Abstract

Optoelectronic realization of adaptive filters and equalizers using fiber optic tapped deIay lines and spatial light modulators has been discussed recently. We describe the design of a single layer fiber optic Adaline neural network which can be used as a bit pattern classifier. In our realization we employ as few electronic devices as possible and use optical computation to utilize the advantages of optics in processing speed, parallelism, and interconnection. The new optical neural network described in this paper is designed for optical processing of guided Iightwave signals, not electronic signals. We analyzed the convergence or learning characteristics of the optically implemented Adaline in the presence of errors in the hardware, and we studied methods for improving the convergence rate of the Adaline.

Paper Details

Date Published: 2 February 1993
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Proc. SPIE 1773, Photonics for Computers, Neural Networks, and Memories, (2 February 1993); doi: 10.1117/12.983198
Show Author Affiliations
Anjan K. Ghosh, Univ. of Iowa (India)
Jim Trepka, Univ. of Iowa (United States)
Palacharla Paparao, Univ. of Iowa (Canada)


Published in SPIE Proceedings Vol. 1773:
Photonics for Computers, Neural Networks, and Memories
Stephen T. Kowel; John A. Neff; William J. Miceli, Editor(s)

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