We use the Hilbert-Huang Transform (HHT) for the spectral analysis of a North-Sea storm that took place in 1997. We look at the contribution of the different Intrinsic Mode Functions (IMF) obtained using the Empirical Mode Decomposition algorithm, and also compare the Hilbert Marginal Spectra and the classical Fourier Spectra for the data set and the corresponding IMFs. We find that the number of IMFs needed to decompose the data and the energy associated to them is different from previous studies for different sea conditions by other authors. A tentative reason for this may lie in the difference in sampling rate used
This study applies a novel concept to decompose water stages to understand the factors that affect a...
A new method for analysing non-linear and non-stationary data has been developed. The key part of th...
This learning object provides a simple explanation of the operation of the Hilbert-Huang transform. ...
We use the Hilbert-Huang Transform (HHT) for the spectral analysis of waves during a storm in the No...
AbstractThe random ocean waves have a natural tendencyto form groups of waves that produced due to t...
To investigate the nonstationary characteristics of strong typhoons, this paper considers the evolut...
In marine sciences, time series are often nonlinear and nonstationary. Their analysis faces new chal...
[1] Data analysis has been one of the core activities in scientific research, but limited by the ava...
Abstract A new method of spectral analysis, using an approach we call the em-pirical mode decomposit...
To accommodate the inherent non-linearity and non-stationarity of many natural time series, empirica...
The Hilbert-Huang transform (HHT) is a method of spectral analysis that is suitable for application ...
Includes bibliographical references (pages 50-51).In this thesis, the Hilbert-Huang Transform will b...
Hilbert-Huang Transform (HHT) is a data analysis tool, first developed in 1998, which can be used to...
Climate is a complicated system containing four topics which are temperature, rainfall, atmospheric ...
The Hilbert Huang Transform is a new technique for the analysis of non–stationary signals. It compri...
This study applies a novel concept to decompose water stages to understand the factors that affect a...
A new method for analysing non-linear and non-stationary data has been developed. The key part of th...
This learning object provides a simple explanation of the operation of the Hilbert-Huang transform. ...
We use the Hilbert-Huang Transform (HHT) for the spectral analysis of waves during a storm in the No...
AbstractThe random ocean waves have a natural tendencyto form groups of waves that produced due to t...
To investigate the nonstationary characteristics of strong typhoons, this paper considers the evolut...
In marine sciences, time series are often nonlinear and nonstationary. Their analysis faces new chal...
[1] Data analysis has been one of the core activities in scientific research, but limited by the ava...
Abstract A new method of spectral analysis, using an approach we call the em-pirical mode decomposit...
To accommodate the inherent non-linearity and non-stationarity of many natural time series, empirica...
The Hilbert-Huang transform (HHT) is a method of spectral analysis that is suitable for application ...
Includes bibliographical references (pages 50-51).In this thesis, the Hilbert-Huang Transform will b...
Hilbert-Huang Transform (HHT) is a data analysis tool, first developed in 1998, which can be used to...
Climate is a complicated system containing four topics which are temperature, rainfall, atmospheric ...
The Hilbert Huang Transform is a new technique for the analysis of non–stationary signals. It compri...
This study applies a novel concept to decompose water stages to understand the factors that affect a...
A new method for analysing non-linear and non-stationary data has been developed. The key part of th...
This learning object provides a simple explanation of the operation of the Hilbert-Huang transform. ...