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

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TLDR
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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Network analysis of exchange data: Interdependence drives crisis contagion

TL;DR: In this paper, the authors detect the linear and nonlinear co-movements presented on the real exchange rate in a group of 28 developed and developing countries that have suffered currency and financial crises during 15 years.
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Multi-step ahead forecasting in electrical power system using a hybrid forecasting system

TL;DR: A novel hybrid forecasting system was successfully developed, including four modules: data preprocessing module, optimization module, forecasting module and evaluation module, which showed that the hybrid system not only can be able to satisfactorily approximate the actual value, but also be regarded as an effective and simple tool adopted in smart grids.
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QRS complex detection using Empirical Mode Decomposition

TL;DR: A new Empirical Mode Decomposition based algorithm for the purpose of QRS complex detection that allows to achieve high detection performances, described by means both the specificity parameters.
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Bolt early looseness monitoring using modified vibro-acoustic modulation by time-reversal

TL;DR: A modified VAM (MVAM) is developed that can circumvent existing problems with practical implementation and provide higher sensitivity in bolt early looseness monitoring, and is compared with the proposed MMSE-based DI with nonlinear DI of traditional VAM method.
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Synchrosqueezing-based time-frequency analysis of multivariate data

TL;DR: The modulated oscillation model is extended to multivariate signals, in order to identify oscillations common to multiple data channels, by introducing a multivariate extension of the synchrosqueezing transform, and using the concept of joint instantaneous frequency multivariate data.
References
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Journal ArticleDOI

Deterministic nonperiodic flow

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.
Book

Linear and Nonlinear Waves

G. B. Whitham
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.
Book

RANDOM DATA Analysis and Measurement Procedures

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.

Theory of communication

Dennis Gabor
Journal ArticleDOI

Mathematical analysis of random noise

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.
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