“Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution matched to its scale. They have advantages over traditional Fourier methods in analyzing physical situations where the signal contains discontinuities and sharp spikes.”
The fractal self-similiarity of the Daubechies mother wavelet.
Copyright
o Amara Graps, 1995-2004
o 1995 by the Institute of Electrical and Electronics Engineers, Inc
The original version of this work appears in IEEE Computational Science and Engineering, Summer 1995, vol. 2, num. 2, published by the IEEE Computer Society


This paper introduces wavelets to the interested technical person outside of the digital signal processing field.”
You may download the paper here,
or
visit the author’s page here.
The author has also written a library or “toolkit” written in IDL that demonstrates wavelet concepts and provides wavelet functions to manipulate data. The library is called “Wavelet Workbench” and can be run from a graphical user interface (“widget”), as demonstrated below:
Wavelet Workbench (WWB).
The library can be found here

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