@inproceedings{abc4682eda424189a938a3dd11d2b32f,
title = "New neural network based sequence estimator in non-Gaussian noise environment",
abstract = "The application of neural network for sequence estimation in the presence of both impulsive noise and intersymbol interference is presented. In this estimator, a nonlinearity is embedded in the conventional steepest descent method for suppressing the impulse noise during the iteration and thus a dual nonlinear steepest descent algorithm is developed for estimating the symbol sequence. This algorithm can be implemented by a recurrent correlation neural network with highly parallel processing. To further improve the performance, a decision feedback technique is developed. It is shown in computer simulations that the new estimator outperforms the linear Viterbi algorithm particularly when there is impulse noise.",
author = "Weng, \{J. F.\} and Leung, \{S. H.\} and Bi, \{G. G.\}",
year = "1996",
language = "English",
volume = "3",
publisher = "IEEE",
pages = "1582--1587",
booktitle = "IEEE International Conference on Neural Networks - Conference Proceedings",
address = "United States",
note = "Proceedings of the 1996 IEEE International Conference on Neural Networks, ICNN. Part 1 (of 4) ; Conference date: 03-06-1996 Through 06-06-1996",
}