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Journal ArticleDOI

The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

TL;DR: In this paper, a new method for analysing nonlinear and nonstationary data has been developed, which is the key part of the method is the empirical mode decomposition method with which any complicated data set can be decoded.
Abstract: A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the empirical mode decomposition method with which any complicated data set can be dec...

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Citations
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Journal ArticleDOI
TL;DR: The intrinsic time-scale decomposition (ITD) as discussed by the authors decomposes a signal into a sum of proper rotation components, for which instantaneous frequency and amplitude are well defined, and a monotonic trend.
Abstract: We introduce a new algorithm, the intrinsic time-scale decomposition (ITD), for efficient and precise time–frequency–energy (TFE) analysis of signals. The ITD method overcomes many of the limitations of both classical (e.g. Fourier transform or wavelet transform based) and more recent (empirical mode decomposition based) approaches to TFE analysis of signals that are nonlinear and/or non-stationary in nature. The ITD method decomposes a signal into (i) a sum of proper rotation components, for which instantaneous frequency and amplitude are well defined, and (ii) a monotonic trend. The decomposition preserves precise temporal information regarding signal critical points and riding waves, with a temporal resolution equal to the time-scale of extrema occurrence in the input signal. We also demonstrate how the ITD enables application of single-wave analysis and how this, in turn, leads to a powerful new class of real-time signal filters, which extract and utilize the inherent instantaneous amplitude and frequency/phase information in combination with other relevant morphological features.

329 citations


Cites methods from "The empirical mode decomposition an..."

  • ...Instead, the sifting process was terminated when the extracted IMFs satisfied the stopping criteria prescribed in Huang et al. (1998). Removing this stopping rule and applying the EMD to the brain wave signal of figure 7c required 56 393 siftings before the very first resulting IMF was produced that...

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  • ...An alternative approach to TFE analysis that made progress towards addressing these difficulties is known as the empirical mode decomposition (EMD; Huang et al. 1998, 2003)....

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  • ...Instead, the sifting process was terminated when the extracted IMFs satisfied the stopping criteria prescribed in Huang et al. (1998)....

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  • ...Finally, and perhaps most importantly, the sifting procedure introduced by Huang et al. (1998) in an attempt to produce proper rotation components with the EMD, but which also causes smearing and smoothing of TFE information, is not needed in the ITD....

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  • ...In an effort to work around this inability to consistently generate proper rotation components, Huang et al. (1998) developed a ‘sifting’ process that is applied in an iterative manner to generate a sequence of signal baseline candidates until one is found with a proper rotation residual....

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Journal ArticleDOI
TL;DR: This study proves that the time complexity of the EMD/EEMD is actually equivalent to that of the Fourier Transform.
Abstract: It has been claimed that the empirical mode decomposition (EMD) and its improved version the ensemble EMD (EEMD) are computation intensive. In this study we will prove that the time complexity of the EMD/EEMD, which has never been analyzed before, is actually equivalent to that of the Fourier Transform. Numerical examples are presented to verify that EMD/EEMD is, in fact, a computationally efficient method.

324 citations

Journal ArticleDOI
TL;DR: In this paper, an Empirical Mode Decomposition/Hilbert-Huang Transformation (EMD/HHT) method was used to separate long-term trends from oscillating modes.
Abstract: [1] Recent studies indicate that the rates of sea level rise (SLR) along the U.S. mid-Atlantic coast have accelerated in recent decades, possibly due to a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) and its upper branch, the Gulf Stream (GS). We analyzed the GS elevation gradient obtained from altimeter data, the Florida Current transport obtained from cable measurements, the North Atlantic Oscillation (NAO) index, and coastal sea level obtained from 10 tide gauge stations in the Chesapeake Bay and the mid-Atlantic coast. An Empirical Mode Decomposition/Hilbert-Huang Transformation (EMD/HHT) method was used to separate long-term trends from oscillating modes. The coastal sea level variations were found to be strongly influenced by variations in the GS on timescales ranging from a few months to decades. It appears that the GS has shifted from a 6–8 year oscillation cycle to a continuous weakening trend since about 2004 and that this trend may be responsible for recent acceleration in local SLR. The correlation between long-term changes in the coastal sea level and changes in the GS strength was extremely high (R = −0.85 with more than 99.99% confidence that the correlation is not zero). The impact of the GS on SLR rates over the past decade seems to be larger in the southern portion of the mid-Atlantic Bight near Cape Hatteras and is reduced northward along the coast. The study suggests that regional coastal sea level rise projections due to climate change must take into account the impact of spatial changes in ocean dynamics.

321 citations


Additional excerpts

  • ...The Empirical Mode Decomposition/HilbertHuang Transform [Huang et al., 1998] is a nonparametric, nonstationary analysis, whereas a time series is decomposed into a finite number of intrinsic oscillatory modes using the local maxima or minima envelope....

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  • ...The analysis method is based on Empirical Mode Decomposition (EMD)/Hilbert-Huang Transformation (HHT) [Huang et al., 1998; Wu and Huang, 2004; Wu et al., 2007; Huang and Wu, 2008]; to the best of our knowledge, the EMD/HHT method has not been used for analyzing sea level trend before it was…...

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Journal ArticleDOI
TL;DR: Results indicate that the proposed model has the potential to obtain a reliable classification of motor imagery EEG signals, and can thus be used as a practical system for controlling a wheelchair.

320 citations

Journal ArticleDOI
TL;DR: The results demonstrate that HHT is suited for capturing transient events in dynamic systems such as the propagation of structural defects in a rolling bearing, thus providing a viable signal processing tool for machine health monitoring.
Abstract: This paper presents a signal analysis technique for machine health monitoring based on the Hilbert-Huang Transform (HHT). The HHT represents a time-dependent series in a two-dimensional (2-D) time-frequency domain by extracting instantaneous frequency components within the signal through an Empirical Mode Decomposition (EMD) process. The analytical background of the HHT is introduced, based on a synthetic analytic signal, and its effectiveness is experimentally evaluated using vibration signals measured on a test bearing. The results demonstrate that HHT is suited for capturing transient events in dynamic systems such as the propagation of structural defects in a rolling bearing, thus providing a viable signal processing tool for machine health monitoring

320 citations


Cites background or methods from "The empirical mode decomposition an..."

  • ...In comparison, the Hilbert–Huang transform (HHT) is based on the instantaneous frequencies resulting from the intrinsic mode functions of the signal being analyzed [ 11 ]–[13]; thus, it is not constrained by the uncertainty limitations with respect to the time and frequency resolutions to which other time-frequency techniques are subject....

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  • ...Equation (13) provides a complete description of the empirical mode decomposition process [ 11 ], which can be evaluated by checking the amplitude error between the reconstructed and the original signal....

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  • ...[ 11 ]. Therefore, the cubic spline function was employed in the presented study....

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  • ...The HHT represents the signal being analyzed in the time-frequency domain by combining the empirical mode decomposition (EMD) with the Hilbert transform [ 11 ]....

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  • ...To effectively construct frequency spectrum of a vibration signal that contains multiple-frequency components, the signal needs to be first decomposed into mono-component functions, by means of EMD [ 11 ]....

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References
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Journal ArticleDOI
TL;DR: In this paper, it was shown that nonperiodic solutions are ordinarily unstable with respect to small modifications, so that slightly differing initial states can evolve into considerably different states, and systems with bounded solutions are shown to possess bounded numerical solutions.
Abstract: Finite systems of deterministic ordinary nonlinear differential equations may be designed to represent forced dissipative hydrodynamic flow. Solutions of these equations can be identified with trajectories in phase space For those systems with bounded solutions, it is found that nonperiodic solutions are ordinarily unstable with respect to small modifications, so that slightly differing initial states can evolve into consider­ably different states. Systems with bounded solutions are shown to possess bounded numerical solutions.

16,554 citations


"The empirical mode decomposition an..." refers background in this paper

  • ...(ii) Lorenz equation The famous Lorenz equation (Lorenz 1963) was proposed initially to study deterministic non-periodic flow....

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Book
01 Jan 1974
TL;DR: In this paper, a general overview of the nonlinear theory of water wave dynamics is presented, including the Wave Equation, the Wave Hierarchies, and the Variational Method of Wave Dispersion.
Abstract: Introduction and General Outline. HYPERBOLIC WAVES. Waves and First Order Equations. Specific Problems. Burger's Equation. Hyperbolic Systems. Gas Dynamics. The Wave Equation. Shock Dynamics. The Propagation of Weak Shocks. Wave Hierarchies. DISPERSIVE WAVES. Linear Dispersive Waves. Wave Patterns. Water Waves. Nonlinear Dispersion and the Variational Method. Group Velocities, Instability, and Higher Order Dispersion. Applications of the Nonlinear Theory. Exact Solutions: Interacting Solitary Waves. References. Index.

8,808 citations

Book
01 Jan 1971
TL;DR: A revised and expanded edition of this classic reference/text, covering the latest techniques for the analysis and measurement of stationary and nonstationary random data passing through physical systems, is presented in this article.
Abstract: From the Publisher: A revised and expanded edition of this classic reference/text, covering the latest techniques for the analysis and measurement of stationary and nonstationary random data passing through physical systems. With more than 100,000 copies in print and six foreign translations, the first edition standardized the methodology in this field. This new edition covers all new procedures developed since 1971 and extends the application of random data analysis to aerospace and automotive research; digital data analysis; dynamic test programs; fluid turbulence analysis; industrial noise control; oceanographic data analysis; system identification problems; and many other fields. Includes new formulas for statistical error analysis of desired estimates, new examples and problem sets.

6,693 citations


"The empirical mode decomposition an..." refers background in this paper

  • ...A brief tutorial on the Hilbert transform with the emphasis on its physical interpretation can be found in Bendat & Piersol (1986)....

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01 Jan 1946

5,910 citations


"The empirical mode decomposition an..." refers methods in this paper

  • ...In order to obtain meaningful instantaneous frequency, restrictive conditions have to be imposed on the data as discussed by Gabor (1946), Bedrosian (1963) and, more recently, Boashash (1992): for any function to have a meaningful instantaneous frequency, the real part of its Fourier transform has…...

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Journal ArticleDOI
TL;DR: In this paper, the authors used the representations of the noise currents given in Section 2.8 to derive some statistical properties of I(t) and its zeros and maxima.
Abstract: In this section we use the representations of the noise currents given in section 2.8 to derive some statistical properties of I(t). The first six sections are concerned with the probability distribution of I(t) and of its zeros and maxima. Sections 3.7 and 3.8 are concerned with the statistical properties of the envelope of I(t). Fluctuations of integrals involving I2(t) are discussed in section 3.9. The probability distribution of a sine wave plus a noise current is given in 3.10 and in 3.11 an alternative method of deriving the results of Part III is mentioned. Prof. Uhlenbeck has pointed out that much of the material in this Part is closely connected with the theory of Markoff processes. Also S. Chandrasekhar has written a review of a class of physical problems which is related, in a general way, to the present subject.22

5,806 citations


"The empirical mode decomposition an..." refers background in this paper

  • ...In general, if more quantitative results are desired, the original skeleton presentation is better; if more qualitative results are desired, the smoothed presentation is better....

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  • ...Therefore, the parameter, ν, defined as N21 −N20 = 1 π2 m4m0 −m22 m2m0 = 1 π2 ν2, (3.7) offers a standard bandwidth measure (see, for example, Rice 1944a, b, 1945a, b; Longuet-Higgins 1957)....

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