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.
Access this part here:
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.
Access this part here:
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.
Access this part here:
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.
Access this part here:
Multiresolution Analysis: The discrete Wavelet transform
You may also access the writer page here

Post to Twitter Post to Yahoo Buzz Post to Delicious Post to Digg Post to Facebook Post to Google Buzz Post to LinkedIn Post to Slashdot Post to StumbleUpon Post to Technorati