An excellent tutorial on Wavelet Analysis covering also the basic concepts of mathematical transformations, time-frequency representations and non-stationary signal properties.
wavelet transform

By Robi Polikar
Dept. of Electrical and Computer Engineering
Rowan University


Part I of this tutorial presents an overview of the basic concepts that are of importance in understanding the wavelet theory. This part summarizes the concept of transforming, and talks about when and why Fourier transform, by far the most often used transform in signal processing, might not be a suitable technique to use.
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Overview: Why wavelet transform?
Part II introduces the Short Term Fourier Transform (STFT), which has been used to obtain time-frequency representations of non-stationary signals. By the end of this part, the reader should be comfortable why and when wavelet transform needs to be used.
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Fundamentals: The Fourier transform and the Short Term Fourier Transform, Resolution problems
Part III introduces the continuous wavelet transform (CWT), explaining how the problems inherent to the STFT are solved. This part gives an introduction to the mathematical backbone of the wavelet transform.
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Multiresolution Analysis: The continuous Wavelet transform
Part IV talks about the discrete wavelet transform, a very effective and fast technique to compute the WT of a signal.
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Multiresolution Analysis: The discrete Wavelet transform
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