One of the main tasks in kernel methods is selection adequate mappings into higher dimension order to improve class classification. However, this tends be time consuming, and it may not finish with best separation between classes. Therefore, there a need for better that are able extract distance from data. This work presents novel approach learning such by using locally stationary kernels, spec...

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...

In this project, Spectral Envelopes in Sound Analysis and Synthesis, various methods for estimation, representation, file storage, manipulation, and application of spectral envelopes to sound synthesis were evaluated, improved, and implemented. A prototyping and testing environment was developed, and a function library to handle spectral envelopes was designed and implemented. For the estimatio...

This thesis describes two algorithms for face detection that rely on a generic feature representation called spectral histogram representation. The sufficiency and generalization of this representation is demonstrated through a statistical sampling technique. It is shown that the spectral histogram representation possesses desirable properties that commonly used representations are lacking. Pre...