Stochastic processes: multiscale processing and applications to signal and image compression
How well can a signal of a certain type be approximated in the spaces V j ? This is typically a linear approximation process, since this approximation can be performed by the projection operator.
How well can a signal of a certain type be approximated by a combination of N wavelets? This, in contrast, is a non-linear approximation process, because we allow the choice of these wavelets to depend on the signal.
Are these approximations better than those that are obtained if we replace the wavelet basis by the trigonometric system?
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