IEICE TRANSACTIONS on Fundamentals
A Novel Grid Occupancy Criterion for Independent Component Analysis
Summary :
Transform each coordinate of the realizations of several random variables (RVs) by the distribution function of the corresponding RV and partition the range space into a uniform grid. The expected number of occupied grid-boxes will be greatest when these RVs are independent. Based on this fact, we propose a novel measure of independence named grid occupancy (GO). We also address the problem of how to make optimum selection of the parameters in GO, i.e., the number of observations and the number of quantization levels. In addition, we apply GO to independent component analysis (ICA). The GO based ICA algorithm can separate signals with arbitrary continuous distributions and favors digital hardware implementation.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E92-A No.8 pp.1874-1882
- Publication Date
- 2009/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E92.A.1874
- Type of Manuscript
- Special Section PAPER (Special Section on Signal Processing)
- Category
- Theory
Authors
Keyword
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Yang CHEN, "A Novel Grid Occupancy Criterion for Independent Component Analysis" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 8, pp. 1874-1882, August 2009, doi: 10.1587/transfun.E92.A.1874.
Abstract: Transform each coordinate of the realizations of several random variables (RVs) by the distribution function of the corresponding RV and partition the range space into a uniform grid. The expected number of occupied grid-boxes will be greatest when these RVs are independent. Based on this fact, we propose a novel measure of independence named grid occupancy (GO). We also address the problem of how to make optimum selection of the parameters in GO, i.e., the number of observations and the number of quantization levels. In addition, we apply GO to independent component analysis (ICA). The GO based ICA algorithm can separate signals with arbitrary continuous distributions and favors digital hardware implementation.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.1874/_p
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@ARTICLE{e92-a_8_1874,
author={Yang CHEN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Novel Grid Occupancy Criterion for Independent Component Analysis},
year={2009},
volume={E92-A},
number={8},
pages={1874-1882},
abstract={Transform each coordinate of the realizations of several random variables (RVs) by the distribution function of the corresponding RV and partition the range space into a uniform grid. The expected number of occupied grid-boxes will be greatest when these RVs are independent. Based on this fact, we propose a novel measure of independence named grid occupancy (GO). We also address the problem of how to make optimum selection of the parameters in GO, i.e., the number of observations and the number of quantization levels. In addition, we apply GO to independent component analysis (ICA). The GO based ICA algorithm can separate signals with arbitrary continuous distributions and favors digital hardware implementation.},
keywords={},
doi={10.1587/transfun.E92.A.1874},
ISSN={1745-1337},
month={August},}
Copy
TY - JOUR
TI - A Novel Grid Occupancy Criterion for Independent Component Analysis
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1874
EP - 1882
AU - Yang CHEN
PY - 2009
DO - 10.1587/transfun.E92.A.1874
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2009
AB - Transform each coordinate of the realizations of several random variables (RVs) by the distribution function of the corresponding RV and partition the range space into a uniform grid. The expected number of occupied grid-boxes will be greatest when these RVs are independent. Based on this fact, we propose a novel measure of independence named grid occupancy (GO). We also address the problem of how to make optimum selection of the parameters in GO, i.e., the number of observations and the number of quantization levels. In addition, we apply GO to independent component analysis (ICA). The GO based ICA algorithm can separate signals with arbitrary continuous distributions and favors digital hardware implementation.
ER -
English
