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        Adaptive electrical signal post-processing with varying representations in optical communication systems

        Author
        Hunt, Stephen
        Sun, Yi
        Shafarenko, Alex
        Adams, Roderick
        Davey, N.
        Slater, Brendan
        Bhamber, Ranjeet
        Boscolo, Sonia
        Turitsyn, Sergei K.
        Attention
        2299/6677
        Abstract
        Improving bit error rates in optical communication systems is a difficult and important problem. Error detection and correction must take place at: high speed, and be extremely accurate. Also, different communication channels have different characteristics, and those characteristics may change over time. We show the feasibility of using simple artificial neural Networks to address these problems; and examine tine effect of using different representations of signal waveforms on the accuracy of error correction. The results we have obtained lead us to the conclusion that a machine learning system based oil these principles cart improve on the performance of existing error correction Hardware at the speed required, whilst being able to adapt to suit; the characteristics of different communication channels.
        Publication date
        2009
        Published in
        Communications in Computer and Information Science
        Published version
        https://doi.org/10.1007/978-3-642-03969-0_22
        Other links
        http://hdl.handle.net/2299/6677
        Relations
        School of Computer Science
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