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Adaptive complex modified probabilistic neural network in digital channel equalization

Young, J.P., Hanselmann, T., Zaknich, A. and Attikiouzel, Y. (2001) Adaptive complex modified probabilistic neural network in digital channel equalization. In: The Seventh Australian and New Zealand Intelligent Information Systems Conference, 18 - 21 November, Perth, Western Australia pp. 247-251.

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Abstract

A novel adaptive technique is proposed for the complex-valued modified probabilistic neural network (MPNN). The adaptive feature is desirable when using the MPNN in channel equalization to track time-varying channels. The MPNN is initially trained using the clustering technique. When training is completed, the network is switched to decision-directed mode and the network parameters are adapted using stochastic gradient-based algorithms in an unsupervised manner. Simulations show that the equalizer was able to efficiently equalize 4-QAM symbol sequences transmitted through nonlinear, slowly time-varying channels.

Publication Type: Conference Paper
Publisher: IEEE
Copyright: © 2001 IEEE
URI: http://researchrepository.murdoch.edu.au/id/eprint/18772
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