Comparative characteristics of the bases of wavelets to represent the speech signals
Keywords:wavelet function of Haar, wavelet "Mexican hat", the conversion of signals
AbstractWavelets allow us to delineate both a low frequency signal characteristics, and high-frequency components. This property is a significant advantage in problems of speech signal processing in comparison with the windowed Fourier transform, where, by varying the width of the window to choose the scale at which you want to highlight features in the signal. Discrete wavelet transform called the representation of signals in the form of a generalized Fourier series in the system of basic functions that arise from some source wavelet due to shift operations in time and change the time scale. The dependence of the relative error of approximation ofthe upper frequency spectrum, normalized to the scalefor two types of signals: the wavelet function and the Haar wavelet "Mexican hat".
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