Mathematics 320 - Wavelet and Fourier Analysis

The first half of the course covers continuous and discrete Fourier transforms (including convolution and Plancherel’s formula), Fourier series (including convergence and the fast Fourier transform algorithm), and applications like heat conduction along a rod and signal processing. The second half of the course is devoted to wavelets: Haar bases, the discrete Haar transform in 1 and 2 dimensions with application to image analysis, multiresolution analysis, filters, and wavelet-based image compression like JPEG2000. Three class hours per week plus a weekly one-hour computer laboratory.

MATH 211 and either MATH 271 or 272, or consent of the instructor is required. Limited to 25 students.

How to handle overenrollment: Preference is given to seniors.

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: Problem sets, Use of computational software, In-class or take-home exams, May include quizzes, group projects, or in-class group work.