The characterization of complex patterns arising from three-phase (e.g., oil–gas–water) flows is an important problem with significant engineering and industrial applications. Based solely on measured conductance fluctuation signals from experimental three-phase flows, we propose a method to...

This paper presents a new algorithm for the analysis of spectral properties of short genes using the wavelet transform and the Hilbert–Huang transform (HHT). A wavelet subspace algorithm combined with the empirical mode decomposition (EMD) is introduced to create subdivided intrinsic mode...

Detrended fluctuation analysis (DFA) is a simple but very efficient method for investigating the power-law long-term correlations of non-stationary time series, in which a detrending step is necessary to obtain the local fluctuations at different timescales. We propose to determine the local...

This study used the Hilbert–Huang transform, a recently developed, instantaneous frequency–time analysis, to analyze radial artery pulse signals taken from women in their 36th week of pregnancy and after pregnancy. The acquired instantaneous frequency–time spectrum (Hilbert spectrum) is...

The objectives are to study and model the aggregate wind power fluctuations dynamics in the multifractal framework. We present here the analysis of aggregate power output sampled at 1 Hz during three years. We decompose the data into several Intrinsic Mode Functions (IMFs) using Empirical Mode...

Determining trend and implementing detrending operations are important steps in data analysis. Yet there is neither precise definition of “trend” nor any logical algorithm for extracting it. In this paper, we propose a Hybrid Detrending Method (HDM) which is based on the Empirical Mode...

Multiscale entropy (MSE) is an effective method to measure the complexity of signals from complex systems, which has been applied to various fields successfully. However, MSE may yield an inaccurate estimate of entropy and induce undefined entropy as the coarse-graining procedure reduces the...

The definition of time is still an open question when one deals with high-frequency time series. If time is simply the calendar time, prices can be modeled as continuous random processes and values resulting from transactions or given quotes are discrete samples of this underlying dynamics. On...

In this work we discuss the problem of price definition when using high frequency foreign exchange data. If one uses the spot mid price a strong autocorrelation of returns, at one lag, is found which is only due to microstructure effect and does not capture the real behavior of price dynamics....