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ICA of Complex Valued Signals: A Fast and Robust Deflationary Algorithm
Como, Italy July 24-July 27
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861330IEEE-INNS-ENNS International Joint Co ...
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Ella Bingham, Aapo Hyvärinen, "ICA of Complex Valued Signals: A Fast and Robust Deflationary Algorithm," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 3, pp. 3357, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3, 2000.
 
 
BibTex
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@article{ 10.1109/IJCNN.2000.861330,
author = {Ella Bingham and Aapo Hyvärinen},
title = {ICA of Complex Valued Signals: A Fast and Robust Deflationary Algorithm},
journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on},
volume = {3},
year = {2000},
issn = {1098-7576},
pages = {3357},
doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861330},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
TI - ICA of Complex Valued Signals: A Fast and Robust Deflationary Algorithm
SN - 1098-7576
SP
EP
A1 - Ella Bingham,
A1 - Aapo Hyvärinen,
PY - 2000
KW - Independent Component Analysis
KW - Complex valued signals
KW - Deflationary separation
VL - 3
JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
ER -
 
Ella Bingham, Helsinki University of Technology
Aapo Hyvärinen, Helsinki University of Technology
Separation of complex valued signals is a frequently arising problem in signal processing. In this article, it is assumed that the original, complex valued source signals are mutually statistically independent, and the problem is solved b y the independent component analysis (ICA) model. ICA is a statistical method for transforming an observed multidimensional random vector in to components that are mutually as independent as possible. In this article, a fast 1/2xed-point type algorithm that is capable of separating complex valued, linearly mixed source signals is presented and simulations show its computational efficiency. We also present a theorem on the local consistency of the estimator given b y the algorithm.
Index Terms:
Independent Component Analysis, Complex valued signals, Deflationary separation
Citation:
Ella Bingham, Aapo Hyvärinen, "ICA of Complex Valued Signals: A Fast and Robust Deflationary Algorithm," ijcnn, vol. 3, pp.3357, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3, 2000
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