Data Signal Processing
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Chapter one, the Fractional Fourier Transforms (FRFT) is introduced.It will show the basis of the FRFT with nostationary behaviors is a chirp-like function related to sinusoid basis of Fourier Transforms. Therefore the FRFT could be considered as the Chirp-like Transforms Chapter two, Curvelet transform is a new multiscale analysis method, and this analysis was developed from the purpose of de-noising. Compare to wavelet, curvelet analysis can solve the characteristic represent of higher dimension and this transform can acquire theoretically the best expression as to curve singularity characte...
Chapter one, the Fractional Fourier Transforms (FRFT) is introduced.It will show the basis of the FRFT with nostationary behaviors is a chirp-like function related to sinusoid basis of Fourier Transforms. Therefore the FRFT could be considered as the Chirp-like Transforms Chapter two, Curvelet transform is a new multiscale analysis method, and this analysis was developed from the purpose of de-noising. Compare to wavelet, curvelet analysis can solve the characteristic represent of higher dimension and this transform can acquire theoretically the best expression as to curve singularity characteristic. Chapter three, a type of time-frequency representation optimal with respect to time-frequency localization is the Wigner Distribution (WD) . The WD is already used to enhance the seismic event .
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