Courses

01:640:357 - Topics in Applied Algebra

Prerequisite: Math 250 Introduction to Linear Algebra and Math 251 Multivariable Calculus.

Introduction to Signal and Image Processing by Discrete Fourier and Wavelet Transforms
This course begins with some topics in linear algebra not covered in Math 250 (such as complex vector spaces, linear transformations, and Fourier series). It then develops the theory of the discrete Fourier transform and the new theory of discrete wavelet transforms. These mathematical tools can separate a digitized audio signal (or two-dimensional image) into low frequency components (coarse outline) and high frequency components (detailed features) in a computationally effective way. Then the signal or image can be compressed or noise can be removed using these components.

The course will involve several MATLAB computer projects. Some prior knowledge of MATLAB is helpful but not necessary. A general familiarity with computers and some basic programming skills are needed. Purchase of MATLAB software is not required, since you can use the MATLAB software in the ARC and other public computer labs at Rutgers. We will also use the public-domain wavelet software package Uvi_Wave (which runs under MATLAB).

Textbook

Textbook:  R. Goodman, Discrete Fourier and Wavelet Transforms: An introduction through Linear Algebra with Applications to Signal Processing (World Scientific, 2016) ISBN: 978-9814625767 (hardcover) 978-9814725774 (softcover) Ebook formats at Amazon and Kobo

Other Resources

Other Recommended Books (not required for course)

A. Jensen and A. la Cour-Harbo, Ripples in Mathematics: The Discrete Wavelet Transform
S. Allen Broughton and Kurt Bryan, Discrete Fourier Analysis and Wavelets
James S. Walker, A Primer on Wavelets and Their Scientific Applications (Second Edition)

Course Materials

Exams