IEICE TRANSACTIONS on Fundamentals
Complex Noisy Independent Component Analysis by Negentropy Maximization
Summary :
The maximization of non-Gaussianity is an effective approach to achieve the complex independent component analysis (ICA) problem. However, the traditional complex maximization of non-Gaussianity (CMN) algorithm does not consider the influence of noise. In this letter, a modification of the fixed-point algorithm is proposed for more practical occasions of the complex noisy ICA model. Simulations show that the proposed method demonstrates significantly improved performance over the traditional CMN algorithm in the noisy ICA model when the sample size is sufficient.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E97-A No.12 pp.2641-2644
- Publication Date
- 2014/12/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E97.A.2641
- Type of Manuscript
- LETTER
- Category
- Noise and Vibration
Authors
Guobing QIAN
University of Electronics Science and Technology of China
Liping LI
University of Electronics Science and Technology of China
Hongshu LIAO
University of Electronics Science and Technology of China
Keyword
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Guobing QIAN, Liping LI, Hongshu LIAO, "Complex Noisy Independent Component Analysis by Negentropy Maximization" in IEICE TRANSACTIONS on Fundamentals,
vol. E97-A, no. 12, pp. 2641-2644, December 2014, doi: 10.1587/transfun.E97.A.2641.
Abstract: The maximization of non-Gaussianity is an effective approach to achieve the complex independent component analysis (ICA) problem. However, the traditional complex maximization of non-Gaussianity (CMN) algorithm does not consider the influence of noise. In this letter, a modification of the fixed-point algorithm is proposed for more practical occasions of the complex noisy ICA model. Simulations show that the proposed method demonstrates significantly improved performance over the traditional CMN algorithm in the noisy ICA model when the sample size is sufficient.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E97.A.2641/_p
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@ARTICLE{e97-a_12_2641,
author={Guobing QIAN, Liping LI, Hongshu LIAO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Complex Noisy Independent Component Analysis by Negentropy Maximization},
year={2014},
volume={E97-A},
number={12},
pages={2641-2644},
abstract={The maximization of non-Gaussianity is an effective approach to achieve the complex independent component analysis (ICA) problem. However, the traditional complex maximization of non-Gaussianity (CMN) algorithm does not consider the influence of noise. In this letter, a modification of the fixed-point algorithm is proposed for more practical occasions of the complex noisy ICA model. Simulations show that the proposed method demonstrates significantly improved performance over the traditional CMN algorithm in the noisy ICA model when the sample size is sufficient.},
keywords={},
doi={10.1587/transfun.E97.A.2641},
ISSN={1745-1337},
month={December},}
Copy
TY - JOUR
TI - Complex Noisy Independent Component Analysis by Negentropy Maximization
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2641
EP - 2644
AU - Guobing QIAN
AU - Liping LI
AU - Hongshu LIAO
PY - 2014
DO - 10.1587/transfun.E97.A.2641
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E97-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2014
AB - The maximization of non-Gaussianity is an effective approach to achieve the complex independent component analysis (ICA) problem. However, the traditional complex maximization of non-Gaussianity (CMN) algorithm does not consider the influence of noise. In this letter, a modification of the fixed-point algorithm is proposed for more practical occasions of the complex noisy ICA model. Simulations show that the proposed method demonstrates significantly improved performance over the traditional CMN algorithm in the noisy ICA model when the sample size is sufficient.
ER -
English
