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Fall 2026
Signals and Systems
ECE 330 Signals and Systems covers time-domain and frequency-domain analysis of continuous and discrete signals and systems using Fourier and Laplace transforms.
Recorded instructors · Fall 2026 Bernie Lesieutre
Summary
1 / 6
Historical reviews of Bernard Lesieutre: The class starts hard but clarifies before midterms. Tests are reasonably difficult but feature a generous curve, and exams closely mirror practice problems.
Grade history
↗ average GPA
letter grades
letter grades
A
AB
B
BC
C
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F
All recorded terms · compare terms & instructors
Prerequisites
Course mapE C E 203 or member of Engineering Guest Students
“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Any of
- ECE 203
- member of Engineering Guest Students
Professors
Fall 2026Historical instructors & teaching patterns
Historical reviews of Bernard Lesieutre: Current instructor Bernie Lesieutre is praised for clear, interesting lectures and generous grading curves, though the material starts difficult. Reviewers note he is smart and accessible for questions, with exams resembling practice problems.
BERNARD LESIEUTRE is recorded teaching in Spring 2009, Fall 2011, Fall 2015, Fall 2019. Recorded history may be incomplete and does not establish a future schedule.
DIMITRIOS PAPAILIOPOULOS is recorded teaching in Spring 2017, Fall 2017, Fall 2018. Recorded history may be incomplete and does not establish a future schedule.
EDUARDO ROMERO ARVELO is recorded teaching in Spring 2020, Spring 2022, Fall 2022, Fall 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.
STARK DRAPER is recorded teaching in Fall 2008, Fall 2012. Recorded history may be incomplete and does not establish a future schedule.
STEVEN FREDETTE is recorded teaching in Fall 2024. Recorded history may be incomplete and does not establish a future schedule.
YU HU is recorded teaching in Fall 2014, Spring 2019. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 104 / 100 | 16 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Meeting source records
Student experience
the class
Historical reviews of Bernard Lesieutre: Bernie Lesieutre is described as clear, interesting, and smart, with exams similar to practice materials. His personality makes the class fun and approachable for questions.
Recent recorded grades — Spring 2025: 3.32 GPA, 62.2% A/AB (n=90 letter grades); Fall 2025: 3.17 GPA, 52.2% A/AB (n=90 letter grades); Spring 2026: 3.22 GPA, 54.3% A/AB (n=94 letter grades).
difficulty & workload
Historical reviews of Bernard Lesieutre: The class starts hard but clarifies before midterms. Tests are reasonably difficult but feature a generous curve, and exams closely mirror practice problems.
Historical reviews of Bernard Lesieutre: Students find Lesieutre easy to talk to and appreciate his clear explanations of tricky content, making the course worth taking despite initial difficulty.
Topics
Skills
Grades
Fall 2026 · Projected
Before grades are released– average GPA
Approximate 80% prediction interval
About this estimate
The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.
The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.
8 earlier forecasts · 0.21 GPA average error.
Grades over time
Through Fall 2026
More grade details Grade mix, volume & source data
Where this course fits relative to
Latest available grades · Spring 2026 · all course levels
GPA
Higher than % of other courses in this group.
Course GPAs · red marks this course’s range
letter grades
More recorded grades than % of other courses in this group.
Typical course in this group: letter grades.
About this comparison
1283 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.
Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.
Sources & history
UW–Madison
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
Observations at scan time; dates do not imply when a catalog change took effect.
Selected offering source records
Signals and Systems
Recorded 2026-09-07Raw records
[
{
"run_id": "20260907T155543-ce3781c4",
"semester": "1272",
"observed_at": "2026-09-07 15:55:43.033547+00:00",
"offering_id": "1272:320:006324",
"course_id": "ECE 330",
"course_uid": "course_1d414842d040e66d0ee9e2ac",
"term_id": "1272",
"source_course_id": "006324",
"source_subject_id": "320",
"title": "Signals and Systems",
"credits_min": 3,
"credits_max": 3,
"typically_offered": "Fall, Spring, Summer"
}
]Rate My Professors
Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
Madgrades
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesModel outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "1bc646718bf5acbb597647f6e1d2d43dcd4e053127386b2ee7aef0822b7ea780",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}