Fundamentals of Wavelets: Theory, Algorithms, and Applications (Google eBook)
Most existing books on wavelets are either too mathematical or they focus on too narrow a specialty. This book provides a thorough treatment of the subject from an engineering point of view. It is a one-stop source of theory, algorithms, applications, and computer codes related to wavelets. This second edition has been updated by the addition of:
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Construction of Wavelets
DWT and Filter Bank Algorithms
2D wavelet application of wavelets approximation B-spline basis functions biorthogonal Chapter coding complex wavelets components compression compute continuous wavelet transform convolution cubic spline curvelet Daubechies decomposition and reconstruction defined discussed dual DWCs electromagnetic example FDTD filter bank finite Fourier series Fourier transform frequency functions and wavelets given grid Haar Haar wavelet IEEE input integral equations interpolation inverse linear spline magnitude matrix method microcalcifications multiresolution multiresolution analysis obtain orthogonal parameter pixel polynomial properties represent representation resolution ridgelet transform samples scaling function semiorthogonal short-time Fourier transform shown in Figure signal processing sinusoid space spectral domain spectrum spline wavelet STFT subband subspaces techniques thresholding time-domain time-frequency window time-scale tion two-scale relation values wavelet analysis wavelet coefficients wavelet decomposition wavelet packets wavelet series Wigner-Ville distribution window function z-transform zero φ φ ψ ψ ω ω