Fourier transform is a series of sine and cosine functions of different frequencies to the decomposition of the original function, after transform the original function in different frequency sine and cosine coefficients. Wavelet transform using a range of different scales of the wavelet decomposition to the original function, after transform the original function coefficients at different scales wavelets. Different wavelet decomposition by translation and scaling, translation is to get the time characteristics of the original function, in order to obtain the frequency scaling characteristics of the original function. Wavelet transform steps: 1. wavelet w (t) and the original function f (t) of the beginning of the comparison, calculate the coefficient C. The coefficient C indicates the degree of similarity of the function and wavelets. 2. Wavelet k units to the right, get the wavelet w (tk), repeat 1. Repeat this end portion know the function f. 3. Extended wavelet w (t), to obtain the

haar_dwt.m
haar_dwt2D.m
main.m

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