Results 151 to 160 of about 5,122,568 (192)
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WEIGHTED SLIDING EMPIRICAL MODE DECOMPOSITION
Advances in Adaptive Data Analysis, 2011The analysis of nonlinear and nonstationary time series is still a challenge, as most classical time series analysis techniques are restricted to data that is, at least, stationary. Empirical mode decomposition (EMD) in combination with a Hilbert spectral transform, together called Hilbert-Huang transform (HHT), alleviates this problem in a purely ...
Faltermeier, R +4 more
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Median ensemble empirical mode decomposition
Signal Processing, 2020Abstract Ensemble empirical mode decomposition (EEMD) belongs to a class of noise-assisted EMD methods that are aimed at alleviating mode mixing caused by noise and signal intermittency. In this work, we propose a median ensembled version of EEMD (MEEMD) to help reduce the additional mode splitting problem of the original EEMD algorithm.
Xun Lang +4 more
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NOISE-MODULATED EMPIRICAL MODE DECOMPOSITION
Advances in Adaptive Data Analysis, 2010The empirical mode decomposition (EMD) is the core of the Hilbert–Huang transform (HHT). In HHT, the EMD is responsible for decomposing a signal into intrinsic mode functions (IMFs) for calculating the instantaneous frequency and eventually the Hilbert spectrum. The EMD method as originally proposed, however, has an annoying mode mixing problem caused
Po-Hsiang Tsui +2 more
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Gap-filling by the empirical mode decomposition
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012We propose a novel gap-filling technique, based on the empirical mode decomposition (EMD). The idea is that a signal with missing data can be decomposed into a set of intrinsic mode functions (IMFs) with missing data. Filling the gaps in each IMF should be easier than filling the gaps in the original signal.
Azadeh Moghtaderi +2 more
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Theoretical Framework for a Succinct Empirical Mode Decomposition
IEEE Signal Processing Letters, 2023Empirical mode decomposition (EMD) lacks a strong theoretical support although extensively applied. We propose a theoretical framework for a succinct EMD in this work, with the assumption of invariant extrema locations for one IMF extraction. We define the envelope mean filter (EMF) and prove that the filter matrix satisfies five properties.
Yang Jin, Zili Li 0003
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EMPIRICAL MODE DECOMPOSITION OF EARTHQUAKE ACCELEROGRAMS
Advances in Adaptive Data Analysis, 2012This article analyzes the strong motion records of past earthquakes by empirical mode decomposition (EMD) technique. The recorded earthquake acceleration time histories are decomposed into a finite number of empirical modes of oscillation. The instantaneous frequency and amplitude of these modes and evolutionary power spectral density (PSD) is ...
S. T. G. Raghukanth, S. Sangeetha
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Empirical mode decomposition on skeletonization pruning
Image and Vision Computing, 2013This paper presents a novel skeleton pruning approach based on a 2D empirical mode like decomposition (EMD-like). The EMD algorithm can decompose any nonlinear and non-stationary data into a number of intrinsic mode functions (IMFs). When the object contour is decomposed by empirical mode like decomposition (EMD-like), the IMFs of the object provide a ...
Stelios Krinidis, Michail Krinidis
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ON THE FILTERING PROPERTIES OF THE EMPIRICAL MODE DECOMPOSITION
Advances in Adaptive Data Analysis, 2010The empirical mode decomposition (EMD) based time-frequency analysis has been used in many scientific and engineering fields. The mathematical expression of EMD in the time-frequency-energy domain appears to be a generalization of the Fourier transform (FT), which leads to the speculation that the latter may be a special case of the former.
Zhaohua Wu, Norden E. Huang
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A sampling limit for the empirical mode decomposition
Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005., 2006The aim of this paper is to investigate the effect of sampling on the empirical mode decomposition (EMD). To this end, an experiment utilising linear frequency modulated (LFM) signals was used to simulate different sampling rates. This experiment showed that as the frequency content of the signal (fc) approached the sampling frequency (fs) the EMD ...
Nathan J. Stevenson +2 more
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Bidimensional Statistical Empirical Mode Decomposition
IEEE Signal Processing Letters, 2012This letter proposes a new algorithm, termed bidimensional statistical empirical mode decomposition (BSEMD) that adopts a smoothing procedure instead of an interpolation when constructing 2-D upper and lower envelopes. For this purpose, we investigate the sifting process effect of conventional bidimensional empirical mode decomposition (BEMD) on the ...
Donghoh Kim, Minjeong Park, Hee-Seok Oh
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