Results 161 to 170 of about 35,860 (209)

Hilbert–Huang Transform and Its Applications

2013
The Hilbert-Huang Transform (HHT) represents a desperate attempt to break the suffocating hold on the field of data analysis by the twin assumptions of linearity and stationarity. Unlike spectrograms, wavelet analysis, or the Wigner-Ville Distribution, HHT is truly a time-frequency analysis, but it does not require an a priori functional basis and ...
Norden E Huang, Samuel S P Shen
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Hilbert-Huang Transform for ECG De-Noising

2007 1st International Conference on Bioinformatics and Biomedical Engineering, 2007
The theories of empirical mode decomposition (EMD) and instantaneous frequency solution which are two parts of Hilbert-Huang Transformation (HHT) are discussed in the paper. We are focus on using the EMD to electrocardiogram (ECG) which can be decomposed into a limited number of intrinsic mode functions. Different thresholds are used to treat intrinsic
Jingtian Tang, Qing Zou, Yan Tang, Bin Liu, Xiao-kai Zhang   +4 more
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Mode Decomposition and the Hilbert-Huang Transform

2019 Russian Open Conference on Radio Wave Propagation (RWP), 2019
The paper presents a relatively new method for the analysis of nonstationary and nonlinear processes called Hilbert-Huang transform. The Hilbert-Huang transform consists of two stages: Empirical mode decomposition and Hilbert Spectral Analysis. The empirical mode decomposition is a signal analysis method that separates multi-component signals into ...
V. D. Ompokov, V. V. Boronoev
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Speech enhancement based on Hilbert-Huang transform

2005 International Conference on Machine Learning and Cybernetics, 2005
The newly developed Hilbert-Huang transform (HHT) is introduced briefly in this paper. The HHT method is specially developed for analyzing nonlinear and non-stationary data. The method consists of two parts: (1) the empirical mode decomposition (EMD), and (2) the Hilbert spectral analysis.
null Zhuo-Fu Liu, null Zhen-Peng Liao, null En-Fang Sang   +2 more
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Robust Kramers–Kronig holographic imaging with Hilbert–Huang transform

Optics Letters, 2023
Holography based on Kramers–Kronig relations (KKR) is a promising technique due to its high-space-bandwidth product. However, the absence of an iterative process limits its noise robustness, primarily stemming from the lack of a regularization constraint.
Xuyang Chang, Cheng Shen, Sitian Liu, Dezhi Zheng, Shuai Wang, Changhuei Yang, Norden E. Huang, Liheng Bian   +7 more
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Speech Detection Based on Hilbert-Huang Transform

First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06), 2006
under strong noise environments, the speech detection often performs bad, in order to make some improvements the Hilbert-Huang Transform is used in the algorithm. The speech signal is decomposed into finite Intrinsic Mode Functions, and then, with the Hilbert transform, the energy-frequency-time distribution of the original signal can be obtained.
Wu Wang, Xueyao Li, Rubo Zhang
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Parallelizing Hilbert-Huang Transform on a GPU

2010 First International Conference on Networking and Computing, 2010
In this paper, we show parallel implementation of Hilbert-Huang Transform on GPU. This implementation focused on the reducing the computation complexity from O(N) on a single CPU to O(N/P log (N)) on GPU, as well as the use of 'shared-global' switching method to increase performance.
Pulung Waskito, Shinobu Miwa, Yasue Mitsukura, Hironori Nakajo   +3 more
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Trend extraction based on Hilbert-Huang transform

2012 8th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP), 2012
Trend extraction is an important tool for the analysis of data sequences. This paper presents a new methodology for trend extraction based on Hilbert-Huang transform. Signals are initially decomposed through use of EMD into a finite number of intrinsic mode functions (IMFs).
null Zhijing Yang, Chris Bingham, null Bingo Wing-Kuen Ling, Michael Gallimore, Paul Stewart, null Yu Zhang   +5 more
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Outlier detection based on Hilbert-Huang Transform

2011 International Conference on Remote Sensing, Environment and Transportation Engineering, 2011
In this paper, we review the main concept and the developing method of Hilbert-Huang Transform (HHT), which is the novel and high-efficiently nonlinear and non-stationary data analysis method. HHT is composed of Empirical Mode Decomposition(EMD) and Hilbert Spectral Analysis(HSA).
null Yan Geng, null Shengjun Xue, Zhiyuan Shen   +2 more
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Hilbert-Huang transform in MHD plasma diagnostics

Plasma Physics Reports, 2005
A new method for processing experimental data from MHD diagnostics is discussed that provides a more detailed study of the dynamics of large-scale MHD instabilities. The method is based on the Hilbert-Huang transform method and includes an empirical mode decomposition algorithm, which is used to decompose the experimental MHD diagnostic signals into a ...
A. M. Kakurin, I. I. Orlovsky
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