Channel Equalization with Cellular Neural Networks
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Date
2010
Authors
Özmen, Atilla
Tander, Baran
Journal Title
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Volume Title
Publisher
IEEE
Abstract
In this paper a dynamic neural network structure called Cellular Neural Network (CNN) is employed for the equalization in digital communication. It is shown that this nonlinear system is capable of suppressing the effect of intersymbol interference (ISI) and the noise at the channel. The architecture is a small-scaled simple CNN containing 9 neurons thus having only 19 weight coefficients. Proposed system is compared with linear transversal filters as well as with a Multilayer Perceptron (MLP) based equalizer.
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Turkish CoHE Thesis Center URL
Citation
0
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Source
Volume
Issue
Start Page
1597
End Page
1599