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Abstract: The stability analysis of blind signal separation algorithms using the threshold nonlinearity is extended to discrete distributions, such as used in digital communication systems. Conditions for the threshold parameter are derived. An extension to the standard algorithm mitigates separation coefficient bias, which is introduced by additive noise at the sensors. Simulations quantify the improvement in terms of steady-state interchannel interference. I. INTRODUCTION The blind separation task... (Update)
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BibTeX entry: (Update)
@misc{ mathis-unbiased,
author = "Heinz Mathis and Marcel Joho",
title = "Unbiased Blind Separation Using the Threshold Nonlinearity",
url = "citeseer.ist.psu.edu/article/mathis01unbiased.html" }
Citations (may not include all citations):11 A simple threshold nonlinearity for blind signal separation - Mathis, Joho et al. - 2000
10 Robust techniques for independent component analysis (ICA) w.. (context) - Cichocki, Douglas et al. - 1998
10 Bias removal technique for blind source separation with nois.. - Douglas, Cichocki et al. - 1998
8 Natural-gradient adaptation (context) - Douglas, Amari - 2000
4 Overdetermined blind source separation: Using more sensors t.. - Joho, Mathis et al. - 2000
3 Adaptive approach to blind source separation with cancellati.. - Cichocki, Kasprzak et al. - 1996
3 Blind separation of mixed-kurtosis signals using an adaptive.. - Mathis, von Hoff et al. - 2000
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