Blind Source Separation Algorithms with Matrix Constraints
Summary :
In many applications of Independent Component Analysis (ICA) and Blind Source Separation (BSS) estimated sources signals and the mixing or separating matrices have some special structure or some constraints are imposed for the matrices such as symmetries, orthogonality, non-negativity, sparseness and specified invariant norm of the separating matrix. In this paper we present several algorithms and overview some known transformations which allows us to preserve several important constraints.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E86-A No.3 pp.522-531
- Publication Date
- 2003/03/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section INVITED PAPER (Special Section on Blind Signal Processing: Independent Component Analysis and Signal Separation)
- Category
- Constant Systems
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Andrzej CICHOCKI, Pando GEORGIEV, "Blind Source Separation Algorithms with Matrix Constraints" in IEICE TRANSACTIONS on Fundamentals,
vol. E86-A, no. 3, pp. 522-531, March 2003, doi: .
Abstract: In many applications of Independent Component Analysis (ICA) and Blind Source Separation (BSS) estimated sources signals and the mixing or separating matrices have some special structure or some constraints are imposed for the matrices such as symmetries, orthogonality, non-negativity, sparseness and specified invariant norm of the separating matrix. In this paper we present several algorithms and overview some known transformations which allows us to preserve several important constraints.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e86-a_3_522/_p
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@ARTICLE{e86-a_3_522,
author={Andrzej CICHOCKI, Pando GEORGIEV, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Blind Source Separation Algorithms with Matrix Constraints},
year={2003},
volume={E86-A},
number={3},
pages={522-531},
abstract={In many applications of Independent Component Analysis (ICA) and Blind Source Separation (BSS) estimated sources signals and the mixing or separating matrices have some special structure or some constraints are imposed for the matrices such as symmetries, orthogonality, non-negativity, sparseness and specified invariant norm of the separating matrix. In this paper we present several algorithms and overview some known transformations which allows us to preserve several important constraints.},
keywords={},
doi={},
ISSN={},
month={March},}
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TY - JOUR
TI - Blind Source Separation Algorithms with Matrix Constraints
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 522
EP - 531
AU - Andrzej CICHOCKI
AU - Pando GEORGIEV
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E86-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2003
AB - In many applications of Independent Component Analysis (ICA) and Blind Source Separation (BSS) estimated sources signals and the mixing or separating matrices have some special structure or some constraints are imposed for the matrices such as symmetries, orthogonality, non-negativity, sparseness and specified invariant norm of the separating matrix. In this paper we present several algorithms and overview some known transformations which allows us to preserve several important constraints.
ER -
English
