Programmable optoelectronic neural network for optimization

Keith J. Symington; Yves Randle; Andrew J. Waddie; Mohammed R. Taghizadeh; John F. Snowdon

doi:10.1364/AO.43.000866

Programmable optoelectronic neural network for optimization

Keith J. Symington, Yves Randle, Andrew J. Waddie, Mohammed R. Taghizadeh, John F. Snowdon

School of Engineering & Physical Sciences

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

An optoelectronic neural network is presented that is designed to solve the assignment problem - or any similar optimization task given minimal adjustment - in both crossbar and banyan packet switches. We examine the design decisions made at the hardware, software, and algorithmic levels and indicate the associated effect on the system as a whole. Clearly detailed experimental results show the system's robustness and performance due to the particular optoelectronic-algorithm combination used. The integration and packaging of such a system are also briefly discussed. © 2004 Optical Society of America.

Original language	English
Pages (from-to)	866-876
Number of pages	11
Journal	Applied Optics
Volume	43
Issue number	4
DOIs	https://doi.org/10.1364/AO.43.000866
Publication status	Published - 1 Feb 2004

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Programmable optoelectronic neural network for optimization

Abstract

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