Linear Systems

ECE 301-003

Fall 2026

NC State University

Instructor. Dror Baron; e-mail: barondror AT ncsu DOT edu; office hour: Wednesdays, 14:45–15:45, Room 2097 EB2 (after class).
Class. Monday and Wednesday, 13:30–14:45, Room 2236 EB3.
Teaching assistant. Xiaowen Tian; e-mail: xtian8 AT ncsu DOT edu; office hour: Fridays 14:00–15:00, EB2 2077.

Announcements

30 August 2026. Course webpage is online; Moodle (NCSU login required).
30 August 2026. HW1 is due on Sep. 4.
30 August 2026. Visual illustrations of aliasing appear below.
1 September 2026. Grade weights have been finalized and posted below. Links to past tests from Dr. Chau-Wai Wong's previous offerings of this course have also been added to the Tests section below. A tentative schedule is now available. Minor updates to the homework due dates have also been made; see below. And HW2 is due on Sep. 11.
10 September 2026. HW3 is due on Sep. 25.

h2>Usef10l Links

Moodle – homework submission, lecture slides, and grades (NCSU login required).
Panopto – lecture recordings (NCSU login required).
Syllabus.
Tentative schedule.
Course materials for ECE 421 (signal processing), ECE 514 (probability and random processes), ECE 512 (data science from a signal processing perspective), ECE/CSC/MA 467/567 (introduction to quantum algorithms).

About this Course

Description

This course provides a rigorous introduction to linear systems theory in both continuous-time (CT) and discrete-time (DT). We develop the mathematical tools—convolution, Fourier series and transforms, the Laplace and z-transforms, and sampling—that underpin signal processing and communications. The course closes with applications to communications systems and an introduction to machine learning.

Prerequisites

C− or better in ECE 220, and either ECE 211 or MUT 303.

Followup Courses

ECE 301 provides the foundation for many subsequent courses, including: ECE 421 (signal processing), ECE 514 (probability and random processes), ECE 512 (data science from a signal processing perspective), ECE 402 (communications), ECE 407 & 470 (computer networking), ECE 308 & 436 (controls), ECE 411 (machine learning), and ECE/CSC/MA 467/567 (introduction to quantum algorithms).

Topics

Below is a list of topics to be covered. The schedule is tentative and may be updated.

Signals and systems: CT and DT signals, energy and power, complex exponentials, impulse and step functions.
System properties: linearity, time-invariance, causality, stability, memory, invertibility.
LTI systems: impulse response, CT and DT convolution, system properties via convolution.
Fourier analysis: CT Fourier series, CT Fourier transform, properties and tables.
Filtering and modulation.
DT Fourier series, DT Fourier transform, DFT and FFT.
Sampling theorem and aliasing.
Laplace transform (bilateral).
z-transform (bilateral).
Application: 2G cellular communications system design.
Introduction to machine learning.

Problem Session

A weekly problem session is organized jointly with Prof. Greg Bottomley's section of ECE 301 and is open to all students.

When: Tuesdays, 15:00–16:00.
Where: FWH 2115.
Zoom: https://ncsu.zoom.us/s/91477812783.
Sessions are recorded; Panopto link to be posted.

Course Materials

Textbook

A. V. Oppenheim and A. S. Willsky, Signals and Systems, Prentice Hall, 2nd edition.

Other

Visual illustration of aliasing; and another video showing "stationary" helicopter blades.

MATLAB

We will use MATLAB for some homework problems. NC State students can download MATLAB here. Here are some resources:

MATLAB tutorial.
Python tutorial (optional alternative).

Assignments and Grading

Grading

Grade weights are as follows.

Component	% of Grade	Notes
Homework:	30%	Two lowest HW grades dropped
Pop quizzes:	10%	Unannounced, in class; two lowest quiz grades dropped
Test 1:	15%	Wednesday, October 7, in class, paper-based
Test 2:	15%	Wednesday, November 18, in class, paper-based
Final exam:	30%	Monday, December 7, 12:00–14:30, in class, paper-based
Extra credit:	Up to 2–3%	Includes bonus problems on homework assignments, plus additional credit at instructor discretion (participation, engagement)

See the syllabus for all course policies.

Homework

Homework is submitted electronically on Moodle by 23:59 on the due date. Attempt problems independently before seeking help. The two lowest homework grades are dropped.

HW1 is due on Sep. 4.
HW2 is due on Sep. 11.
HW3 is due on Sep. 25.
HW4 is due on Oct. 9.
HW5 is due on Oct. 23.
HW6 is due on Nov. 6.
HW7 is due on Nov. 20.

Key Dates

Event	Date	Notes
Labor Day	Monday, September 7	No class
Wellness Day	Tuesday, September 29	No class
Test 1	Wednesday, October 7	In class, paper-based
Fall Break	Monday, October 19	No class
Test 2	Wednesday, November 18	In class, paper-based
Thanksgiving break	Wednesday–Friday, November 25–27	No class
Final Exam	Monday, December 7, 12:00–14:30	In class, paper-based

Tests

Past tests from previous offerings of this course are available on Dr. Chau-Wai Wong's course pages. On each page, scroll down to the class schedule table: midterm exam papers are linked inline under the label “exam paper,” and the final exam is linked under “Final Exam.”

Spring 2021 – two midterms.
Spring 2022 – two midterms.
Spring 2023 – two midterms and a final exam.
Spring 2024 – two midterms and a final exam.

Feedback

Students are encouraged to send feedback to Prof. Baron, barondror dot {gmail dot com, ncsu dot edu}.