ECE 401 Signal Processing, Fall 2026¶
Introduction to signal processing for advanced undergraduates or graduate students in the biological, physical, social, engineering and computer sciences. Representation and processing of continuous-time and discrete-time signals and images using phasors, Fourier series, sampling, FIR filters, discrete-time Fourier transform, Z transform, and IIR filters. Machine problems include processing of music, speech, photographic image, bioelectric, and biomedical image data.
4 undergraduate hours. 4 graduate hours. Prerequisite: MATH 220.
Credit is not given for both ECE 310 and ECE 401.
Recommended Text: DSPFirst by McClellan, Schafer and Yoder, 2nd edition, 2016.
Instructor: Mark Hasegawa-Johnson (jhasegaw).
Teaching Assistant: Zhihao Huang (zihaoh5).
Contents:
On-line Tools¶
CampusWire will be used for on-line question answering. If you need the code to enter this site, send an e-mail to the course instructors.
Gradescope is used for machine problems and exams.
PrairieLearn will be used for daily quizzes.
- Lectures can be viewed online in either of two ways:
Synchronously using zoom. The zoom link is on CampusWire.
Asynchronously using MediaSpace.
DSPFirst Demos contains useful demos.
Our logo this semester is a Nyquist sampling demo uploaded by Jacopo Bertolotti.
Grades¶
Grade cutoffs are approximately: 90% for A-, 75% for B-, 60% for C-. Your cumulative score for the semester is a weighted sum of component scores, with the following weights:
25.0%: Daily quizzes
30.0%: Machine problems
15.0%: Exam 1
15.0%: Exam 2
15.0%: Exam 3
Any machine problem or daily quiz may be turned in late, with a penalty of 5%.
Extra credit is available for correctly answering the questions of other students on CampusWire. This counts for up to 1% of your cumulative semester grade.
- AI Policy: You must attempt each problem once on your own, and run
the code using either the Jupyter notebook or grade.py, before asking an AI for help.
