Results 181 to 190 of about 98,906 (246)

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
openaire   +1 more source

Underwater Acoustic Target Recognition Based on Hilbert–Huang Transform and Data Augmentation

IEEE Transactions on Aerospace and Electronic Systems
This article proposes an underwater acoustic target recognition method using the Hilbert–Huang transform (HHT) and data augmentation, with a residual convolutional neural network (CNN) as the classifier.
Qihai Yao, Yong Wang, Yixin Yang
semanticscholar   +1 more source

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
openaire   +1 more source

Winding deformation classification in a power transformer based on the time-frequency image of frequency response analysis using Hilbert-Huang transform and evidence theory

International Journal of Electrical Power & Energy Systems, 2021
This study presents a novel fully-automated technique to interpret a frequency response analysis (FRA) of a power transformer, using a combined method based on digital image processing and evidence theory.
A. Shamlou, M. Feyzi, V. Behjat
semanticscholar   +1 more source

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
openaire   +2 more sources

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
openaire   +1 more source

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
openaire   +1 more source