Well, I'm very interested in this topic aswell. I can't tell you
everything but a few things: A Wavelet transform is a
generalization/improvement to a Fourier Transform. If you
Fourier Transform a signal, you essentially turn time into
frequency and frequency into time. The use of this is manifold.
It helps computers understanding inputs like humans do for one
part. (what we hear is essentially processed by a fourier
transform to perform grouping of information and such) It can be
used to compress data (there is data that, while corresponding
to a function that's hard to calculate, has fairly easy fourier
representation), it's frequently used to proove things in maths
and physics. Overally, Wavelets already helped in a LOT of
applications and continue to do so. However, while BEFORE
Fourier transformation, you only have the information, when you
reach what value, AFTER it, you only have the information,
essentially how often you reach what value. Some applications
need BOTH informations. To do that, Wavelet t