Spring 2027

Signals and Systems

Covers time/frequency domain analysis of signals and systems using Fourier, Laplace, and z-transforms, plus sampling and convolution.

offering recorded3 credits
Recorded instructors · Spring 2027 Eduardo Romero Arvelo

Summary

1 / 6

Past student reviews · Eduardo Arvelo

The course required students to work through in-class activities to learn the concepts needed for exams, supported by pre-class video lectures.

What you’ll be able to do

  • Determine whether a system is linear, time-invariant, stable, and/or causal

  • Convert between time-domain and frequency-domain representations of signals

  • Analyze the behavior of continuous-time and discrete-time systems using time-domain and frequency-domain techniques

  • Compute and evaluate single-input single-output transfer functions from differential and difference equations

  • Perform discrete-time processing of continuous-time signals using sampling, filtering, and reconstruction

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

E C E 203 or member of Engineering Guest Students

    • ECE 203
    • member of Engineering Guest Students
    take one
ECE 330 used by

“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

Spring 2027

Past student reviews · Eduardo Arvelo

Eduardo Romero Arvelo taught ECE 330 using a semi-flipped learning style with video and in-person lectures. Students reported feeling prepared for in-class activities and exams after his classes.

Recent recorded grades — Fall 2022: 3.16 GPA, 50.0% A/AB (n=72 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).

Historical instructors & teaching patterns

Past student reviews · Bernard Lesieutre, Dimitris Papailiopoulos

Bernard Lesieutre explained tricky content clearly, and exams were reasonably difficult with a generous curve. Dimitris Papailiopoulos was friendly and explained complicated problems during WisCEL exercises.

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

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 1000

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

Past student reviews · Eduardo Arvelo

Eduardo Romero Arvelo taught ECE 330 using a semi-flipped learning style, combining video lectures with in-person sessions to prepare students for in-class activities and exams.

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

Past student reviews · Eduardo Arvelo

The course required students to work through in-class activities to learn the concepts needed for exams, supported by pre-class video lectures.

Past student reviews · Eduardo Arvelo

One student found Eduardo to be a wonderful lecturer, noting that the combination of video and in-person lectures left them well-prepared for class activities.

Topics

  • Time-domain response and convolution
  • Frequency-domain response with Fourier and Laplace transforms
  • Discrete Fourier methods, sampling, and z-transform

Skills

  • Converting between time-domain and frequency-domain signal representations
  • Discrete-time processing of continuous-time signals via sampling and filtering
  • Computing SISO transfer functions from differential and difference equations

Grades

Historical instructor

Spring 2027 · 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 · 0.11 GPA average error.

Grades over time

Through Spring 2027

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

1280 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.

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Selected offering source records
ECE 330 · Spring 2027

Signals and Systems

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:320:006324",
    "course_id": "ECE 330",
    "course_uid": "course_1d414842d040e66d0ee9e2ac",
    "term_id": "1274",
    "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
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "59d6e74cb5d233ae9e954097c1ba4a0185fe69394ced90a142f8b30657b46225",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}