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Wavelet Tutorial_Classic0(2)

'Wavelet Tutorial_Classic0(2)'
WELCOME WELCOME Welcome to The Wavelet Tutorial ! It was end of October 1994. I had recently studied fundamentals of wavelet transform as my graduation project at my undergraduate institution, and I was planning to use this technique in analyzing signals of biological origin for my Master's degree thesis. My major professor suggested that I should work on EEG signals, since they are less studied compared to many other biological signals. This, of course, would require a databa other biological signals. This, of course, would require a database of EEG signals. I was in desperate need of finding a database of EEG signals when I decided to use this project for my Master's degree thesis, Multiresolution Wavelet Analysis Multiresolution Wavelet Analysis of Event Related Potentials for the Detection of Alzheimer's Disease of Event Related Potentials for the Detection of Alzheimer's Disease . The hospitals were refusing to cooperate in sharing their files, stating that all patient files were confidential. I have then decided to search the Internet hoping to find people who may have a database that might be of any use to me. I told them that I would use the wavelet transform to analyze EEG signals, and asked them if they had such data to share with me. The majority of the mails I have received from them were of the type: Sorry! We do not have any EEG data , but what is this wavelet business anyway? If you can provide some information, we may be able to direct you . So I replied and tried to explain what I was after. It didn't take me too long to realize that I was writing a 4-6 pages of information on wavelet transform all over again every time someone asked for more information. Furthermore, since most of those people were from the medical community and had little or no background in signal processing, I had to start from the definition of a transform. Trying to explain a relatively new signal processing technique backed with a highly complex mathematical theory, starting from the definition of the transform was no easy task. One thing I suffered while I was learning the basics of the wavelet transform is the fact that the majority of the articles and books (if not all of them) are written by math people, for the math people, in a language which even most of the math people themselves cannot understand what is going on. I remember that I got frustrated with all those equations, trying to figure out how and where to use them. I was so frustrated at that time that I decided to write my own book in some day. When I received so many mails about the wavelet transform, I thought that writing a tutorial could be a starting point for my future dream of writing my own book of wavelet trasforms. I knew that I had to put it in simple words to make it understandable to those people. This is how this tutorial was first created. In the first version of the tutorial, there were absolutely no equations, and it simply consisted of basic concepts what wavelet transf
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WaveletTutorial_Classic0(2)
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