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Wavelet and Hilbert-Huang transform used in cardiology
Proceedings of the 2014 6th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), 2014A pacemaker is a small electronic device implanted under the skin near the collarbone. Pacemakers monitor the heart's electrical activity. If the heart is beating too slowly or pausing too long between beats, the pacemaker will provide electrical impulses that stimulate the heart to beat.
Milan Stork, Vlastimil Vancura
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SEARCHING FOR GRAVITATIONAL WAVES WITH THE HILBERT–HUANG TRANSFORM
Advances in Adaptive Data Analysis, 2009Gravitational waves are a consequence of Einstein's theory of general relativity applied to the motion of very dense and massive objects such as black holes and neutron stars. Their detection will reveal a wealth of information about these mysterious objects that cannot be obtained with electromagnetic probes.
Jordan B. Camp +3 more
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Speech Detection Based on Hilbert-Huang Transform
First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06), 2006under 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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A survey on Hilbert-Huang transform: Evolution, challenges and solutions
Digital Signal Processing, 2022Abstract Signal processing methods are essential in scientific research, and time-frequency analysis techniques such as Fourier Transform constitute an important progress in data analysis, but may be limited to examining non-linear and non-stationary processes, although there are ways to work around this problem, with Wavelet Transform for example ...
Uender Barbosa de Souza +2 more
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Trend extraction based on Hilbert-Huang transform
2012 8th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP), 2012Trend 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).
Zhijing Yang +5 more
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Effect of the Hilbert-Huang transform method on sleep staging
2017 25th Signal Processing and Communications Applications Conference (SIU), 2017Sleep scoring is performed by examining the recorded electroencephalogram (EEG) and some other signals recorded by a polysomnography (PSG) device. This process is considered more reliable as it is done manually by experts. However, due to the fact that experts may also be mistaken, it has led to an increase in the importance given to automatic sleep ...
Yucelbas, Cuneyt +4 more
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Research of Hilbert Huang Transform Algorithm and its Improvement
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020Hilbert Huang transform (HHT) is a kind of time-frequency analysis method. It has been widely used because of its adaptability of empirical modal process and the integrity of feature extraction[1]. However, there are some defects in it. The two problems of end-point winging and extreme point fitting are obvious.
Jingxin Luo, Jianyang Tang
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Speech pitch determination based on Hilbert-Huang transform
Signal Processing, 2006Pitch determination is an essential part of speech recognition and speech processing. In this paper, a new pitch determination method based on Hilbert-Huang Transform (HHT) is presented. The assumption of linearity of the speech-production process and short-time stationarity of speech signals, which is generally employed in recent studies on speech ...
Hai Huang, Jiaqiang Pan
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Hilbert–Huang Transform Approach to Lorenz Signal Separation
Advances in Adaptive Data Analysis, 2015This study uses the Hilbert–Huang transform (HHT), a signal analysis method for nonlinear and non-stationary processes, to separate signals of varying frequencies in a nonlinear system governed by the Lorenz equations. Similar to the Fourier series expansion, HHT decomposes a data time series into a sum of intrinsic mode functions (IMFs) using ...
Gregori J. Clarke, Samuel S. P. Shen
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Classification of ingestion sounds using Hilbert-huang transform
2017 25th Signal Processing and Communications Applications Conference (SIU), 2017Automatic classification of food ingestion gives a precise and objective solution for dietary monitoring which is an active research area. In this study, we aim to classify ingestion sounds of the six different food types recorded from the throat microphone.
M. A. Tugtekin Turan, Engin Erzin
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