Neural Networks for Identification, Prediction, and Control
Neural Networks for Identification, Prediction, and Control
Maximum margin equalizers trained with the Adatron algorithm
Signal Processing
Blind equalization of constant modulus signals using support vector machines
IEEE Transactions on Signal Processing
Online pattern classification with multiple neural network systems: an experimental study
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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In this paper, we propose a new recursive classifier based on a recurrent neural network. A supervised algorithm is employed to estimate the classifier parameters. The proposed classifier is used to form a non-linear Decision Feedback Equalizer (DFE) for communication channels. A new procedure allowing the estimation of the decision delay is also presented so that the classifier parameters and the decision delay are estimated at the same time. This new DFE leads to suitable equalization performances even in presence of non-linear and non-minimum phase channels.