Over the past twenty years there has been an ever increasing interest in the subject of wavelets, cutting across traditional scientific boundaries. EE-274 continues to be designed to accommodate students in mathematics, statistics, computer science, physics and of course, engineering. What students desiring to take the course should have, is some background in Fourier theory. What students should bring to the course is a strong interest in seeing the resolution of data analysis problems by methods beyond the Fourier domain. EE-274 constitutes an engineering science elective for EEs. It is also co-listed as Math 278. Basic digital signal processing will be reviewed during the first two weeks.

EE-274 has been undergoing ``revision'' each of the five times it has been taught since 1997. For Spring 2007 we plan a few more changes. We will be working in MATLAB with real data using both Fourier and wavelet-based decompositions. Specifically, we will analyze 3 practical problems in some depth. Mathematical integrity will, however, not be sacrificed. One problem will be in electrocardiology, where we have substantial amounts of a atrial fibrillation data. The other may be in Elastography where we also have access to real data. If there is active student interest, we may consider looking at a problem in modeling turbulent flow. Other applications are being considered. There will be 3 guest lectures in each of the 3 application areas.

There is no one adequate text for the course. Lectures will be from notes, gleaned from research and from many texts. This year, we will also use the text,``Wavelet Methods for Time Series Analysis''. A number of examples such as (i) a subtidal sea level series (ii) Nile River minima series (iii) ocean shear series (iv) solar magnetic field data (v) NMR spectrum are provided in the text and we will analyze them. With additional examples and four ``case studies" in MATLAB's Wavelet User's Guide, Chapter 4 (p.318), there will be a very generous exposure to applications.


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