This course at the University of Michigan will introduce you to fundamental concepts needed in order to work with discrete-time signals. The world is continuous, but in order to capture, process, and manipulate signals on a computer, we must convert the continuous world into discrete time. The topics we will cover begin with the discrete-time Fourier series and transforms and sampling/converting signals from continuous time to discrete time. We will also cover the Z-transform, filter response, and filter design. With time we will learn about 2D filters, autoregressive models, and signal decomposition. The course ends with a group project on a topic of your choosing. The output of that project is signal processing code and a website describing the project. These projects have been highlighted multiple times in EECS news:
June 2022 story
August 2015 story
Here are the past year's project websites:
DSP EECS 351 student projects for Winter 2023
DSP EECS 351 student projects for Winter 2022
DSP EECS 351 student projects for Fall 2020
DSP EECS 351 student projects for Winter 2019
DSP EECS 351 student projects for Fall 2016
DSP EECS 351 student projects for Fall 2015
DSP student projects for Fall 2014
DSP student projects for Fall 2013
We use canvas and Piazza for this class. Please see canvas for the syllabus, homeworks, lecture notes, etc. Please use Piazza for your questions.