Nonlinear channel equalization using multilayer perceptrons with information-theoretic criterion
D Erdogmus, D Rende, JC Principe… - Neural networks for …, 2001 - ieeexplore.ieee.org
Neural networks for signal processing XI: proceedings of the 2001 …, 2001•ieeexplore.ieee.org
The minimum error entropy criterion was recently suggested in adaptive system training as
an alternative to the mean-square-error criterion, and it was shown to produce better results
in many tasks. The authors apply a multilayer perceptron scheme trained with this
information theoretic criterion to the problem of nonlinear channel equalization. In our
simulations, we use a realistic nonlinear channel model, which is encountered when
practical power amplifiers are used in the transmitter. The bandwidth-efficient 16-QAM …
an alternative to the mean-square-error criterion, and it was shown to produce better results
in many tasks. The authors apply a multilayer perceptron scheme trained with this
information theoretic criterion to the problem of nonlinear channel equalization. In our
simulations, we use a realistic nonlinear channel model, which is encountered when
practical power amplifiers are used in the transmitter. The bandwidth-efficient 16-QAM …
The minimum error entropy criterion was recently suggested in adaptive system training as an alternative to the mean-square-error criterion, and it was shown to produce better results in many tasks. The authors apply a multilayer perceptron scheme trained with this information theoretic criterion to the problem of nonlinear channel equalization. In our simulations, we use a realistic nonlinear channel model, which is encountered when practical power amplifiers are used in the transmitter. The bandwidth-efficient 16-QAM scheme, which uses a dispersed constellation, is assumed.
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