In the Mari field, 3D seismic, conventional attribute methodologies on the full stack, broadband data set showed an ambiguous fault definition. Frequency Spectral Decomposition has been applied on Mari 3D seismic data and generated attribute maps, which exhibited substantially more fidelity than full-bandwidth, conventional attributes. It has been found that fault definition is superior to conv...

The analysis of nonlinear and nonstationary time series is still a challenge, as most classical time series analysis techniques are restricted to data that is, at least, stationary. Empirical mode decomposition (EMD) in combination with a Hilbert spectral transform, together called Hilbert-Huang transform (HHT), alleviates this problem in a purely data-driven manner. EMD adaptively and locally ...

Harmonic wavelets have simple formulations in the fi-equency domain and they have proved a good basis for the time-frequency mapping of transient signals. Moreover their computational algorithm allows bandwidth to be chosen arbitrarily so that they offer a variable Q transform, where Q is the ratio of centre frequency to bandwidth. In contrast, the short-time Fourier transform and the Wlgner-Vi...

In very low rate coding the aim is to accurately represent speech characteristics as efficiently as possible. High coding gains for the spectral features can be achieved through the use of temporal decomposition. Waveform interpolation coders accurately represent the excitation using characteristic waveforms (CWs) extracted at a constant rate. In this paper, the two approaches are combined into...

Disease identification is a major task in the field of biomedical. To perform it the analysis of EEG signal is to be performed. The proposed method presents for feature extraction from electroencephalogram (EEG) signals using empirical mode decomposition (EMD). Its use is motivated by the fact that the EMD gives an effective time-frequency analysis of nonstationary signals. The intrinsic mode f...

In this paper, we develop domain decomposition spectral method for mixed inhomogeneous boundary value problems of high order differential equations defined on unbounded domains. We introduce an orthogonal family of new generalized Laguerre functions, with the weight function x , α being any real number. The corresponding quasiorthogonal approximation and Gauss-Radau type interpolation are inves...

Category decomposition method based on matched filter for un-mixing of mixed pixels: mixels which are acquired with spaceborne based hyperspectral radiometers is proposed. Through simulation studies with simulated mixed pixels which are created with spectral reflectance data derived from USGS spectral library as well as actual airborne based hyperspectral radiometer imagery data, it is found th...

An approach to estimate the number of rules by spectral analysis of the training dataset has been recently proposed [1]. This work presents an analysis of such a method in high performance computing environment. Two approaches for parallel implementation of the method were studied considering the structure selection genetic algorithm and the spectral decomposition. The results show that both ap...

Spectral CT is a promising new imaging modality that is able to provide spectral information of several pre-selected energy ranges in one image acquisition, which allows quantitative decomposition of multiple materials. In addition to conventional reconstruction, novel decomposition techniques should be developed to realize material separation. Decomposition of multienergy X-ray data into basis...