Abstract
Artificial neural network equaliser architectures offer advantages over transversal equaliser architectures. One of these advantages is the capacity for generalisation and the introduction of highly non-linear properties in the transfer function of the equaliser. When the equalisation is non-linear, as in the case of dispersive communications channels, artificial neural network structures have been shown to offer improved performance over transversal models, as reported in [2], [7], [8] for non-time-varying channels. Results for time-varying channels are also given in [3], [4].
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Soto, I., Carrasco, R.A. (1997). Combination of a Viterbi Decoder with an Adaptive Neural Equaliser Over a Rician Fading Channel. In: Wysocki, T., Razavi, H., Honary, B. (eds) Digital Signal Processing for Communication Systems. The Springer International Series in Engineering and Computer Science, vol 403. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-6119-4_22
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DOI: https://doi.org/10.1007/978-1-4615-6119-4_22
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