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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 for saliency detection
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation, 2012We propose a novel method for saliency detection and attention selection inspired by processes in the human visual cortex. To mimic the varying spatial resolution of the human eye as well as the constant eye movements (saccades) and to model the effect of temporal adaptiveness, we use empirical mode decomposition and corresponding intrinsic mode ...
Maja Rudinac +2 more
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Empirical Mode Decomposition for Trivariate Signals
IEEE Transactions on Signal Processing, 2010An extension of empirical mode decomposition (EMD) is proposed in order to make it suitable for operation on trivariate signals. Estimation of local mean envelope of the input signal, a critical step in EMD, is performed by taking projections along multiple directions in three-dimensional spaces using the rotation property of quaternions.
Naveed ur Rehman, Danilo P. Mandic
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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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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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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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Enhanced Empirical Mode Decomposition
2008Empirical mode decomposition (EMD) associated with the Hilbert-Huang transform (HHT) deconstructs a time-series signal into a set of monocomponent signals called intrinsic mode functions (IMF). EMD also acts as a filter limiting the frequency range of each IMF. EMD filtering is less than ideal and can lead to misleading results.
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Hierarchical decomposition based on a variation of empirical mode decomposition
Signal, Image and Video Processing, 2016Adaptive methods of signal analysis have proved a very useful tool for analysis of non-stationary signals. This is due to the ability of these methods to adapt to the local structures of the signals being analysed, as these methods are not constrained by a fixed basis.
Muhammad Kaleem +2 more
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Selective Noise Empirical Mode Decomposition
IEEE Signal Processing LettersWe propose selective noise empirical mode decomposition (SNEMD), an adaptive noise-assisted technique that enhances the performance of empirical mode decomposition (EMD) by introducing calibrated complementary noise and selectively extracting optimal modes.
Songhua Liu +3 more
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BANDWIDTH EMPIRICAL MODE DECOMPOSITION AND ITS APPLICATION
International Journal of Wavelets, Multiresolution and Information Processing, 2008There are some methods to decompose a signal into different components such as: Fourier decomposition and wavelet decomposition. But they have limitations in some aspects. Recently, there is a new signal decomposition algorithm called the Empirical Mode Decomposition (EMD) Algorithm which provides a powerful tool for adaptive multiscale analysis of ...
Qiwei Xie +5 more
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