ECE-688
ARRAY PROCESSING
Not in Fall 2026
Term
Overview
Feedback is mixed. The clearest upside is that teaching clarity stands out. Best for students who want a structured class rather than chaos. The sample is still thin, so treat this as directional rather than definitive.
DepartmentELEC&CMP
Terms offeredSpring
Typical enrollment13–13
Semesters of data1
5.5
Hrs / week
6
Responses
13
Enrollment
46%
Response Rate
Evaluation Scores
Overall quality
Teaching, content, and experience combined.
3.7
Intellectually stimulating
Challenges students to think deeply.
4.0
Instructor effectiveness
Explains concepts and facilitates learning.
4.0
Difficulty
Higher means harder.
3.7
Feedback Analysis
Feedback Analysislow
Analysis based on student evaluations
Based on 16 comments across 1 sections
Feedback is mixed. The clearest upside is that teaching clarity stands out. Best for students who want a structured class rather than chaos. The sample is still thin, so treat this as directional rather than definitive.
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
• Teaching clarity stands out; students repeatedly say the material is explained clearly and effectively.
Tradeoffs
• There is no single dominant complaint theme, but the feedback is not uniformly glowing either.
Best fit for
Best for students who want a structured class rather than chaos.
Watch out for
• Most of the signal comes from a limited sample, so be careful about over-generalizing.
• A large share of the evidence comes from one instructor's version of the course, so this may not generalize cleanly.
Student Responses
I learned about array processing, specifically beamforming, adaptive filter theory and gradient descent approach through this course.
Spring 2025 · Krolik, Jeffrey
- The interpretation of a beamformer as a spatial frequency filter with connections to classical FIR filter design - Foundational beamformers- MVDR/GSC, Optimal Beamformer and the associated required knowledge/tradeoffs - Experience with processing traditional chirped radar data - An introduction to foundational adaptive filtering and recursive bayesian estimation- the Weiner filter, Kalman filter, LMS algorithm
Spring 2025 · Krolik, Jeffrey
Throughout this course, I developed a deeper understanding of space-time signal processing, adaptive filter applications and state estimation, which are really helpful for my research and study.
Spring 2025 · Krolik, Jeffrey
I definitely have better knowledge about radar, including different ways to improve the recieved SNR, and adaptive filters. Good improvement in math, algebra, optimization. I am also more capable in stress resistance.
Spring 2025 · Krolik, Jeffrey
Rating History
Rating history
Error bars show \u00B11 std dev
| Term | Instructor | Overall | Difficulty | Hrs/wk | Enrolled |
|---|---|---|---|---|---|
| Spring 2025 | Krolik, Jeffrey | 3.7 | 3.7 | 5.5 | 13 |
Instructor
Krolik, JeffreyELEC&CMP
Also teaches
ECE-485 DIGITAL AUDIO PROCESSING2.6