MA 349

Signals & Systems (Spring 2025)

Textbook: "Linear Algebra, Signal Processing, and Wavelets - A Unified Approach : MATLAB Version" by Øyvind Ryan, 2019, Springer. 

Online Access through Purdue Library: https://purdue.primo.exlibrisgroup.com/permalink/01PURDUE_PUWL/uc5e95/alma99169502244501081 

You can also use the Python version of the textbook:  "Linear Algebra, Signal Processing, and Wavelets - A Unified Approach : Python Version" by Øyvind Ryan, 2019, Springer. Library Link: https://purdue.primo.exlibrisgroup.com/permalink/01PURDUE_PUWL/uc5e95/alma99169502228701081 

About the course: This course introduces the mathematical framework for the description, analysis and processing of signals such as music, speech and images. Main topics covered include signal representations in different bases; continuous-time signal sampling; and signal processing by linear and time invariant systems.

Learn the math behind important data science algorithms like: Convolution, the Fast Fourier Transform, Denoising, Compression, Edge Detection, and Wavelets.

Using Edge Detection on an image of Joseph Fourier. 

Here’s how MA 34900 fits into mathematics degree requirements:

• Applied Math Majors: It can replace MA 42800 as a required course.
• Data Science/Math Majors: It can substitute for CS 34800.
• Other Math Majors and Minors: It counts as a selective in the Computer Science area.

Corresponding Data Science Lab:

This course has a corresponding 1-credit lab course:

MA 34990: The Data Science Labs Signals and Systems

Explore the applications of signal processing using sound and music.

(Clockwise from top left) A picture of Fourier, Edge detection on Fourier, Blurring on Fourier, and Embossing on Fourier.