Spring 2027

Signals, Information, and Computation

Intro to signals, information, and computation in EE. Covers Fourier series, DFT, sampling, digital filters, and coding for signal manipulation.

offering recorded3 credits
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 6

Past student reviews · Bernard Lesieutre

Exams were described as fairly straightforward if students completed the review assignment and period exercises. Preparing adequately for class was considered sufficient for success.

What you’ll be able to do

  • Manipulate complex numbers in the context of representing sinusoids

  • Represent periodic continuous-time signals using the Fourier series

  • Represent finite-duration discrete-time signals using the discrete Fourier transform

  • Determine sampling parameters for analog-to-digital conversion of signals

  • Apply digital filters to discrete-time signals

  • Write code using numerical computing software to manipulate signals

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

(MATH 211, 217, or 221) or member of Engineering Guest Students

ECE 203 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

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

BERNARD LESIEUTRE is recorded teaching in Spring 2013, Fall 2021, Spring 2023, Fall 2023, Spring 2025. Recorded history may be incomplete and does not establish a future schedule.

CHUNG-HAN HSIEH is recorded teaching in Fall 2017. Recorded history may be incomplete and does not establish a future schedule.

EDUARDO ROMERO ARVELO is recorded teaching in Fall 2020, Spring 2022, Fall 2022, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

FENG YE is recorded teaching in Fall 2023, Fall 2024, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

JOHN GUBNER is recorded teaching in Spring 2015, Fall 2015, Spring 2016. Recorded history may be incomplete and does not establish a future schedule.

MIKKO LIPASTI is recorded teaching in Fall 2020. Recorded history may be incomplete and does not establish a future schedule.

ROBERT NOWAK is recorded teaching in Fall 2012, Fall 2024. Recorded history may be incomplete and does not establish a future schedule.

YU HU is recorded teaching in Spring 2017, Fall 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 / 1100
LEC 002Classroom Instruction0 / 900

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

The course uses a flipped classroom model where students watch lectures independently and participate in in-class activities. Professor Arvelo circulates during sessions to assist with questions.

Recent recorded grades — Spring 2025: 3.46 GPA, 70.9% A/AB (n=141 letter grades); Fall 2025: 3.49 GPA, 76.1% A/AB (n=209 letter grades); Spring 2026: 3.43 GPA, 69.0% A/AB (n=184 letter grades).

difficulty & workload

Past student reviews · Bernard Lesieutre

Exams were described as fairly straightforward if students completed the review assignment and period exercises. Preparing adequately for class was considered sufficient for success.

Past student reviews · Eduardo Arvelo

Professor Arvelo was noted for genuinely caring about student understanding, helping learners grasp concepts rather than just memorizing answers. He was available to help during class activities.

Topics

  • Signals, information, and computational techniques
  • Complex numbers and sinusoids
  • Fourier series
  • Discrete Fourier transform
  • Sampling and analog-to-digital conversion
  • Digital filters

Skills

  • Manipulate complex numbers for sinusoid representation
  • Represent periodic continuous-time signals with Fourier series
  • Represent finite-duration discrete-time signals with DFT
  • Determine sampling parameters for A/D conversion
  • Apply digital filters to discrete-time signals
  • Write code using numerical computing software to manipulate signals

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 · 0.25 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.

Download part 1
Selected offering source records
ECE 203 · Spring 2027

Signals, Information, and Computation

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": "1274:320:023741",
    "course_id": "ECE 203",
    "course_uid": "course_1c943aa88ab6f61c9fa4c558",
    "term_id": "1274",
    "source_course_id": "023741",
    "source_subject_id": "320",
    "title": "Signals, Information, and Computation",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Fall, Spring"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Download part 1
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": "19eb80b4e09b13f15b04af549aa0f4e9c3599838df2e1a34ca1cb9244913f211",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}