Abstract
In this paper we investigate the application of a combined Genetic Programming – Simulated Annealing (GP-SA) solution to a classical signal processing problem which arises in communications systems. This is the so called channel equalisation problem where the task is to construct a system which adaptively compenstates for imperfections in the path from the transmitter to the receiver. Our primary interest is to examine the recosntruction of binary data sequences transmitted through distorting channels. We measure the performance of a generic GP-SA equaliser and compare it to that of standard methods commonly used in real systems. In particular, we consider special cases which are known to be difficult for the existing methods, such as non-linear and partial response channels. Our results show that the GP-SA method generally offers superior signal restoration but at the expense of computational effort.
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Esparcia-Alcázar, A., Sharman, K. (1999). Genetic Programming for Channel Equalisation. In: Poli, R., Voigt, HM., Cagnoni, S., Corne, D., Smith, G.D., Fogarty, T.C. (eds) Evolutionary Image Analysis, Signal Processing and Telecommunications. EvoWorkshops 1999. Lecture Notes in Computer Science, vol 1596. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10704703_10
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DOI: https://doi.org/10.1007/10704703_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65837-5
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