IEICE TRANSACTIONS on Fundamentals
A Study of the Characteristics of MEMD for Fractional Gaussian Noise
Summary :
The dyadic filter bank property of multivariate empirical mode decomposition (MEMD) for white Gaussian noise (WGN) is well established. In order to investigate the way MEMD behaves in the presence of fractional Gaussian noise (fGn), we conduct thorough numerical experiments for MEMD for fGn inputs. It turns out that similar to WGN, MEMD follows dyadic filter bank structure for fGn inputs, which is more stable than empirical mode decomposition (EMD) regardless of the Hurst exponent. Moreover, the estimation of the Hurst exponent of fGn contaminated with different kinds of signals is also presented via MEMD in this work.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E99-A No.6 pp.1228-1232
- Publication Date
- 2016/06/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E99.A.1228
- Type of Manuscript
- LETTER
- Category
- Digital Signal Processing
Authors
Huan HAO
PLA University of Science and Technology
Huali WANG
PLA University of Science and Technology
Naveed UR REHMAN
COMSATS Institute of Information Technology
Hui TIAN
PLA University of Science and Technology
Keyword
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Huan HAO, Huali WANG, Naveed UR REHMAN, Hui TIAN, "A Study of the Characteristics of MEMD for Fractional Gaussian Noise" in IEICE TRANSACTIONS on Fundamentals,
vol. E99-A, no. 6, pp. 1228-1232, June 2016, doi: 10.1587/transfun.E99.A.1228.
Abstract: The dyadic filter bank property of multivariate empirical mode decomposition (MEMD) for white Gaussian noise (WGN) is well established. In order to investigate the way MEMD behaves in the presence of fractional Gaussian noise (fGn), we conduct thorough numerical experiments for MEMD for fGn inputs. It turns out that similar to WGN, MEMD follows dyadic filter bank structure for fGn inputs, which is more stable than empirical mode decomposition (EMD) regardless of the Hurst exponent. Moreover, the estimation of the Hurst exponent of fGn contaminated with different kinds of signals is also presented via MEMD in this work.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E99.A.1228/_p
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@ARTICLE{e99-a_6_1228,
author={Huan HAO, Huali WANG, Naveed UR REHMAN, Hui TIAN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Study of the Characteristics of MEMD for Fractional Gaussian Noise},
year={2016},
volume={E99-A},
number={6},
pages={1228-1232},
abstract={The dyadic filter bank property of multivariate empirical mode decomposition (MEMD) for white Gaussian noise (WGN) is well established. In order to investigate the way MEMD behaves in the presence of fractional Gaussian noise (fGn), we conduct thorough numerical experiments for MEMD for fGn inputs. It turns out that similar to WGN, MEMD follows dyadic filter bank structure for fGn inputs, which is more stable than empirical mode decomposition (EMD) regardless of the Hurst exponent. Moreover, the estimation of the Hurst exponent of fGn contaminated with different kinds of signals is also presented via MEMD in this work.},
keywords={},
doi={10.1587/transfun.E99.A.1228},
ISSN={1745-1337},
month={June},}
Copy
TY - JOUR
TI - A Study of the Characteristics of MEMD for Fractional Gaussian Noise
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1228
EP - 1232
AU - Huan HAO
AU - Huali WANG
AU - Naveed UR REHMAN
AU - Hui TIAN
PY - 2016
DO - 10.1587/transfun.E99.A.1228
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E99-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2016
AB - The dyadic filter bank property of multivariate empirical mode decomposition (MEMD) for white Gaussian noise (WGN) is well established. In order to investigate the way MEMD behaves in the presence of fractional Gaussian noise (fGn), we conduct thorough numerical experiments for MEMD for fGn inputs. It turns out that similar to WGN, MEMD follows dyadic filter bank structure for fGn inputs, which is more stable than empirical mode decomposition (EMD) regardless of the Hurst exponent. Moreover, the estimation of the Hurst exponent of fGn contaminated with different kinds of signals is also presented via MEMD in this work.
ER -
English
