  The wavelet transform and related techniques are used to analyze singular and
fractal signals. The normalized wavelet scalogram is introduced to detect
singularities including jumps, cusps and other sharply changing points. The
wavelet auto-covariance is applied to estimate the self-similarity exponent for
statistical self-affine signals.
