Correcting errors in optical data transmission using neural networks


Optical data communication systems are prone to a variety of processes that modify the transmitted signal, and contribute errors in the determination of 1s from 0s. This is a difficult, and commercially important, problem to solve. Errors must be detected and corrected at high speed, and the classifier must be very accurate; ideally it should also be tunable to the characteristics of individual communication links. We show that simple single layer neural networks may be used to address these problems, and examine how different input representations affect the accuracy of bit error correction. Our results lead us to conclude that a system based on these principles can perform at least as well as an existing non-trainable error correction system, whilst being tunable to suit the individual characteristics of different communication links.

Event Title: 20th International Conference on Artificial Neural Networks – ICANN 2010
Event Type: Other
Event Location: Thessaloniki
Event Dates: 2010-09-15 - 2010-09-18
Uncontrolled Keywords: error correction, classification, optical communication, adaptive signal processing, Computer Science(all), Theoretical Computer Science
ISBN: 3-642-15821-8
Last Modified: 23 Oct 2019 12:24
Date Deposited: 13 Sep 2012 07:14
Published Date: 2010
Authors: Hunt, Stephen
Sun, Yi
Shafarenko, Alex
Adams, Rod
Davey, Neil
Slater, Brendan
Bhamber, Ranjeet
Boscolo, Sonia
Turitsyn, Sergei K.


Item under embargo.

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