ECE-581

RANDOM SIGNALS AND NOISE

Offered Fall 2026
ELEC&CMP · Taught by Pfister, Henry · Last offered Fall 2025
Term
Instructor

Overview

Feedback is mostly positive. The strongest signal is that students generally rate the course well. Best for students who are genuinely interested in the topic and willing to engage with the course on its own terms.

DepartmentELEC&CMP
Terms offeredFall
Typical enrollment12–48
Semesters of data3
6.5
Hrs / week
40
Responses
94
Enrollment
43%
Response Rate

Evaluation Scores

Overall quality
Teaching, content, and experience combined.
4.2
12345
Intellectually stimulating
Challenges students to think deeply.
4.1
12345
Instructor effectiveness
Explains concepts and facilitates learning.
4.3
12345
Difficulty
Higher means harder.
3.4
12345

Feedback Analysis

Feedback Analysishigh
Analysis based on student evaluations
Based on 40 comments across 3 sections

Feedback is mostly positive. The strongest signal is that students generally rate the course well. Best for students who are genuinely interested in the topic and willing to engage with the course on its own terms.

Student Reports
How hard is the A?
A is doable but not automatic
The signal here is more do-the-work-and-you-should-be-fine than easy-A chatter. Students do not describe the A as automatic, but the evidence also does not paint grading as punishing.
Homework Load
Moderate homework load
Homework load looks moderate. The recurring signal is steady weekly work, but not a course that turns every assignment into a grind.
Lecture Load
Regular lecture load
Lectures matter here, but the evidence points to a fairly standard lecture burden rather than a course dominated by long or exceptionally dense lectures.
Strengths
Instructor ratings are strong even when the comments do not cluster around one obvious positive theme.
Tradeoffs
There is no single dominant complaint theme, but the feedback is not uniformly glowing either.
Best fit for
Best for students who are genuinely interested in the topic and willing to engage with the course on its own terms.

Student Responses

Refresh my memory for math foundation for machine learning
Fall 2024 · Richmond, Christ
Multivariate probability, stochastic processes, and statistical signal processing.
Fall 2024 · Richmond, Christ
I become stronger in mathematical derivation
Fall 2024 · Richmond, Christ
Probability, random process, collaboration
Fall 2024 · Richmond, Christ
Random Vector and MSE are things that I found interesting and enjoyed during class. Also, things like distribution I often use for my other class as well.
Fall 2024 · Richmond, Christ

Rating History

Rating history
Error bars show \u00B11 std dev
TermInstructorOverallDifficultyHrs/wkEnrolled
Fall 2025Pfister, Henry5.412
Fall 2024Richmond, Christ 0.0Rate My ProfessorsQuality0.0Difficulty0.0Based on 0 ratingsClick to view on RMP →4.23.46.848
Fall 2023Richmond, Christ 0.0Rate My ProfessorsQuality0.0Difficulty0.0Based on 0 ratingsClick to view on RMP →7.534

Instructor

Pfister, HenryELEC&CMP
Also teaches
ECE-586D VECTOR SPACE METHODS APPL4.1ECE-587 INFORMATION THEORY4.1