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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: In this article, the authors demonstrate the importance of representing aerosols, and their indirect effects, in general circulation models, and suggest that intermodel diversity in aerosol burden and representation of aerosol-cloud interaction can produce substantial variation in simulations of climate variability on multi-decadal timescales.
Abstract: Analysis of single forcing runs from CMIP5 (the fifth Coupled Model Intercomparison Project) simulations shows that the mid-twentieth century temperature hiatus, and the coincident decrease in precipitation, is likely to have been influenced strongly by anthropogenic aerosol forcing. Models that include a representation of the indirect effect of aerosol better reproduce inter-decadal variability in historical global-mean near-surface temperatures, particularly the cooling in the 1950s and 1960s, compared to models with representation of the aerosol direct effect only. Models with the indirect effect also show a more pronounced decrease in precipitation during this period, which is in better agreement with observations, and greater inter-decadal variability in the inter-hemispheric temperature difference. This study demonstrates the importance of representing aerosols, and their indirect effects, in general circulation models, and suggests that inter-model diversity in aerosol burden and representation of aerosol–cloud interaction can produce substantial variation in simulations of climate variability on multi-decadal timescales.

152 citations

Journal ArticleDOI
TL;DR: The objective is to qualitatively explore how well BEMD is able to smooth an image for more effective edge detection with the Sobel method.
Abstract: Crack evaluation is essential for effective classification of pavement cracks. Digital images of pavement cracks have been analyzed using techniques such as fuzzy set theory and neural networks. Bidimensional empirical mode decomposition (BEMD), a new image analysis method recently developed, can potentially be used for pavement crack evaluation. BEMD is an extension of the empirical mode decomposition (EMD), which can decompose nonlinear and nonstationary signals into basis functions called intrinsic mode functions (IMFs). IMFs are monocomponent functions that have well-defined instantaneous frequencies. EMD is a sifting process that is nonparametric and data driven; it does not depend on an a priori basis set. It is able to remove noise from signals without complicated convolution processes. BEMD decomposes an image into two-dimensional IMFs. The present paper explores pavement crack detection using BEMD together with the Sobel edge detector. A number of images are filtered with BEMD to remove noise, and the residual image analyzed with the Sobel edge detector for crack detection. The results are compared with results from the Canny edge detector, which uses a Gaussian filter for image smoothing before performing edge detection. The objective is to qualitatively explore how well BEMD is able to smooth an image for more effective edge detection with the Sobel method.

152 citations


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

  • ...[7] gives the full treatment of the HHT method....

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  • ...Two stopping criteria have been proposed: a Cauchy-type convergence that depends on limiting the standard deviation computed from two consecutive IMFs [7], and one that depends on the agreement of the numbers of extrema and zero crossings [8]....

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Journal ArticleDOI
TL;DR: In this article, a hybrid early-warning system was successfully developed, composed of forecasting and evaluation, based on the theory of decomposition and ensemble and combined with the advanced data processing technique, support vector machine, the latest bio-inspired optimization algorithm and the leave-one-out strategy for deciding weights.

152 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the robustness and accuracy of various trend detection methods such as ordinary least squares, robust and generalized linear model regression, Ensemble Empirical Mode Decomposition (EEMD), and wavelets.
Abstract: This study investigates the significance of trends offourtemperature time series—Central EnglandTemperature (CET), Stockholm, Faraday-Vernadsky, and Alert. First the robustness and accuracy of various trend detection methods are examined: ordinary least squares, robust and generalized linear model regression, Ensemble Empirical Mode Decomposition (EEMD), and wavelets. It is found in tests with surrogate data that these trend detection methods are robust for nonlinear trends, superposed autocorrelated fluctuations, and non-Gaussian fluctuations. An analysis of the four temperature time series reveals evidence of long-range dependence (LRD) and nonlinear warming trends. The significance of these trends is tested against climate noise. Three different methods are used to generate climate noise: (i) a short-range-dependent autoregressive process of first order [AR(1)], (ii) an LRD model, and (iii) phase scrambling. It is found that the ability to distinguish the observed warming trend from stochastic trends depends on the model representing the background climate variability. Strong evidence is found of a significant warming trend at Faraday-Vernadsky that cannot be explained by any of the three null models. The authors find moderate evidence of warming trends for the Stockholm and CET time series that are significant against AR(1) and phase scrambling but not the LRD model. This suggests that the degree of significance of climate trends depends on the null model used to represent intrinsic climate variability. This study highlights that in statistical trend tests, more than just one simple null model of intrinsic climate variability should be used. This allows one to better gaugethe degree of confidence to havein the significance of trends.

152 citations


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

  • ...EMD and EEMD have been shown to be able to extract nonlinear trends in climatic time series (e.g., Huang et al. 1998; Wu et al. 2007; Wu and Huang 2009; Wu et al. 2011; Franzke 2009, 2010; Franzke and Woollings 2011; Qian et al. 2011)....

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  • ...…when the distribution of the residuals is nonGaussian and known. d. EEMD The Ensemble Empirical Mode Decomposition method (Wu and Huang 2009; Huang et al. 1998; Huang and Wu 2008; Wu et al. 2007; Qian et al. 2009; Franzke 2010) decomposes a time series into a finite number of intrinsic mode…...

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  • ...First the robustness and accuracy of various trend detection methods are examined: ordinary least squares, robust and generalized linear model regression, Ensemble Empirical Mode Decomposition (EEMD), and wavelets....

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  • ...Also, the EEMD trends are nonlinear and very similar to the cubic fits (Fig....

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  • ...In practice, the algorithm has to be refined by a so-called sifting process (e.g., Huang et al. 1998), which amounts to iterating steps (i)–(iii) until this can be considered a zero mean to some stopping criterion (Huang et al. 1998; Rilling et al. 2003)....

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Journal ArticleDOI
TL;DR: This study presents a novel micro-grid protection scheme based on Hilbert-Huang transform (HHT) and machine learning techniques, which proves the effectiveness and reliability of the proposed micro- grid protection scheme.
Abstract: This study presents a novel micro-grid protection scheme based on Hilbert-Huang transform (HHT) and machine learning techniques. Initialisation of the proposed approach is done by extracting the three-phase current signals at the targeted buses of different feeders. The obtained non-stationary signals are passed through the empirical mode decomposition method to extract different intrinsic mode functions (IMFs). In the next step using HHT to the selected IMFs component, different needful differential features are computed. The extracted features are further used as an input vector to the machine learning models to classify the fault events. The proposed micro-grid protection scheme is tested for different protection scenarios, such as the type of fault (symmetrical, asymmetrical and high impedance fault), micro-grid structure (radial and mesh) and mode of operation (islanded and grid connected) and so on. Three different machine learning models are tested and compared in this framework: Naive Bayes classifier, support vector machine and extreme learning machine. The extensive simulated results from a standard IEC micro-grid model prove the effectiveness and reliability of the proposed micro-grid protection scheme.

152 citations


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

  • ...The discrete HT is calculated by utilising transfer function and the DFT [17]....

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  • ...2, pp. 388-397 © The Institution of Engineering and Technology 2017 391 The discretise transform transfer function is described as H(ω) = −J 0 ω π 0 ω = 0 and ω = π J − π ω 0 (10) The discrete HT is calculated by utilising transfer function and the DFT [17]....

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  • ...The range of SD value is considered as 0.2–0.3 as rightly suggested by Huang and Shen [17], for the shifting process of difference between two consecutive shifting....

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  • ...The complete procedure for applying HT is given below: Step 1: Apply DFT to the signal S(k). where, k = 1, 2… ....

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  • ...As stated by Huang and Shen in [17], an IMF is presented as a function that fulfils the succeeding two preconditions:...

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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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