Instructor: Jon Wilkening

Lectures: TTh 11-12:30, Room 71 Evans

Course Control Number: 54491

Office: 1091 Evans

Office Hours: Tues 9:45-10:45, Tues 3-4

Prerequisites: Math 53 and 54 or equivalent

Required Text: A First Course in Wavelets with Fourier Analysis, by Boggess and Narcowich

Recommended Reading:
Wavelets Made Easy, by Yves Nievergelt
A Wavelet Tour of Signal Processing, by Stephane Mallat

Syllabus: This course will cover the basic mathematical theory and practical applications of Fourier analysis and wavelets, including one-dimensional signal processing and multi-dimensional image processing:

• Fourier series, orthogonal systems, sampling and aliasing, FFT
• Fourier integrals and transforms, linear filters, sampling theorem, uncertainty principle, two-dimensional Fourier analysis
• Haar wavelets, Daubechies wavelets, scaling functions, multiresolution analysis, filter banks
• approximation with wavelets, linear and nonlinear techniques, image approximation and adaptive basis selection, edge detection
• transform coding, signal compression, quantization, high bit-rate compression, image and video compression

Course Webpage: /~wilken/118.S09

Grading:

homework:	50%
Midterm:	20%	Tues, March 10, in class
Final exam:	30%	Tues, May 19, 8-11 AM, 4 Evans. (2 pages of notes allowed.)

Homework: 8-10 assignments, some involving programming in Matlab