in this paper some new applications of empirical mode decomposition (emd) and hilbert spectrum in seismic ground-roll attenuation, random noise attenuation and spectral decomposition are introduced. hilbert spectrum is a time-frequency representation for hilbert-huang transform which is obtained by combination of instantaneous frequency (if) concept and intrinsic mode function of empirical mode...

For the analysis of time series data from hydrology, we employ a technique recently developed in Huang et al., 1998, which is by now widely known as the Hilbert-Huang-Transform (HHT). Specifically, it is designed for nonlinear and nonstationary data. In contrast to data analysis techniques employing the short-time/windowed Fourier transform or the continuous wavelet transform, the new technique...

The parameters in a nuclear magnetic resonance (NMR) free induction decay (FID) signal contain information that is useful in magnetic field measurement, magnetic resonance sounding (MRS) and other related applications. A real time sampled FID signal is well modeled as a finite mixture of exponential sequences plus noise. We propose to use the Hilbert-Huang Transform (HHT) for noise reduction an...

Abstract In this paper, the Innovative Trend Methodology (ITM) and their inspired approaches, i.e., Double (D-ITM) Triple (T-ITM), were combined with Hilbert Huang transform (HHT) time frequency-based method. The new hybrid methods (i.e., ITM-HHT, D-ITM-HHT, T-ITM-HHT) proposed compared to DWT-based in order recommend best Three total annual rainfall series from 1920 2011 selected three hydrolo...

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent the Fast Fourier Transform (FFT). Both carry strong a-priori assumptions about the source data, such as linearity, of being stationary, and of satisfjmg the Dirichlet conditions. A recent development at the National Aeronautics an...

The Hilbert-Huang Transform is a novel, adaptive approach to time series analysis that does not make assumptions about the data form. Its adaptive, local character allows the decomposition of non-stationary signals with hightime-frequency resolution but also renders it susceptible to degradation from noise. We show that complementing the HHT with techniques such as zero-phase ltering, kernel de...

Hilbert-Huang Transform (HHT) is a data analysis tool, first developed in 1998, which can be used to extract the periodic components embedded within oscillatory data. This thesis is dedicated to the understanding, application, and development of this tool. First, the background theory of HHT will be described and compared with other spectral analysis tools. Then, a number of applications will b...

Pipeline networks are one of the most important transportation for gas, oil and water. Leakage in pipelines results extensive financial loss. To avoid this situation, an algorithm based on Empirical Mode Decomposition method (EMD) Hilbert-Huang Transform (HHT) is presented research. The objectives research to detect leakage by using EMD locate location leak HHT method. focuses Galvanized Iron (...

Tidal power generation technology has advanced quickly in recent years. In this study, the Hilbert-Huang transform (HHT) was used to examine electrical energy distribution law of tidal according time periods days, months, and years based on observed data for generation. Our analysis summarized as follows: span one day, motor ran 14 h before shutting off 10 h. The frequency 28 Hz, maximum voltag...

Temperature, solar radiation and water are major important variables in ecosystem models which are measurable via wireless sensor networks (WSN). Effective data analysis is necessary to extract significant spatial and temporal information. In this work, information regarding the long term variation of seasonal field environment conditions is explored using Hilbert-Huang transform (HHT) based an...