UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN

Department of Electrical and Computer Engineering

ECE 310: Digital Signal Processing (Fall 2026)

Course Description:

Introduction to discrete-time systems and discrete-time signal processing with an emphasis on causal systems; discrete-time linear systems, difference equations, z-transforms, discrete convolution, stability, discrete-time Fourier transforms, analog-to-digital and digital-to-analog conversion, digital filter design, discrete Fourier transforms, fast Fourier transforms, spectral analysis, and applications of digital signal processing.

Course Prerequisite:

ECE 210

I. Teaching Staff

1. Instructors:

Prof. Farzad Kamalabadi (Sec. CCS) Prof. Corey Snyder (Sec. E)
Office: 320 CSL Office: ECEB 2058
Email: farzadk@illinois.edu Email: cesnyde2@illinois.edu

2. Teaching Assistants:

(Head TA) Ethan Ran Nick Bampton Jung Ki Lee Mia Onodera Hao Zhang
Email: eran2@illinois.edu Email: bampton2@illinois.edu Email: jungkil2@illinois.edu Email: mco7@illinois.edu Email: haoz19@illinois.edu

II. Schedule

1. Lectures:

Lecture Time Day Location
Section CCS 12:00 p.m. - 12:50 p.m. M W F ECEB 3017
Section E 3:00 pm. - 3:50 p.m. M W F ECEB 1002

2. Office Hours (starting 8/31):

All office hours are held in ECEB 2034 unless noted otherwise.

Time Monday Tuesday Wednesday Thursday Friday
9-10 a.m.          
10-11 a.m.       Hao  
11 a.m.-12 p.m.   Jung Ki   Hao Jung Ki
12-1 p.m. Lecture Jung Ki Lecture   Lecture
1-2 p.m. Ethan   Nick Prof. Snyder Ethan
2-3 p.m.     Nick   Ethan
3-4 p.m. Lecture Mia Lecture Mia Lecture
4-5 p.m.   Mia      
5-6 p.m.          
6-7 p.m.          

III. Resources

1. Recommended Textbook:

2. Course Campuswire:

3. Associated Lab Course (Strongly recommended):

4. Additional Resources

The following additional resources cover much of the same material as the lectures and textbook. The syllabus below provides references to these resources as well as the Manolakis and Ingle textbook.

5. Lecture Resources

Section CCS (12:00pm Section)

Mediaspace Recordings Link

Section E (3:00pm Section)

Mediaspace Recordings Link

Box Folder with Lecture Notes and Slides

IV. Syllabus

Time Topics Reading Assignment Additional Resources Assessment Due
Week 1:
8/24 - 8/28		 Course introduction
Continuous-time (CT) and discrete-time (DT) signals
Review of complex numbers
Discrete-time systems
Linear and time-invariant (LTI) systems

 

 Chapter 1: 1.1 - 1.4
Chapter 2: 2.1 - 2.3		 SM: Ch 1, Appendix D, Appendix A, 3.1, 3.3-3.6
OS: 1, 2.1-2.2
PM: 1.1-1.2, 2.1-2.2
FK: 1, 5, 2, 9
Python Demo
What is DSP? - Video by IEEE
DSP at UIUC - 1
DSP at UIUC - 2		  
Week 2:
8/31- 9/4		 No class 9/7 (Labor Day)
Impulse response
Convolution
Difference equations		 Chapter 2: 2.4 - 2.7; 2.10

SM: 3.7-3.9
OS: 2.3-2.5
PM: 2.3-2.5
FK: 9, 10, 3
Convolution Python Demo
Difference Equations Python Demo

 HW1
 
Week 3:
9/7 - 9/11		 z-transform
Poles and zeros
Inverse z-transform		 Chapter 3: 3.1 - 3.4 SM: 4.1-4.5
OS: Ch 3
PM: 3.1-3.5
FK: 6, 7, 8 13
Partial Fractions Python Demo
Some z-transform properties
Some z-transform pairs		 HW2
 
Week 4:
9/14 - 9/18

Quiz 1 Period

System analysis via z-transform
System transfer function
Stability

 Chapter 3: 3.5 - 3.7 SM: 4.10-4.14
OS: 5.2
PM: 3.6
FK: 14, 15, 16
Stability Python Demo		 HW3
 
Week 5:
9/21 - 9/25		 Applications of linear system models
Sinusoidal signals
Fourier transforms
Discrete-time Fourier transform (DTFT)		 Chapter 4: 4.1 - 4.3 SM: 2.1-2.4
OS: 2.6-2.7 PM: 1.3, 4.1
FK: 17
Inverse Filter Python Demo
Applications of Linear System Theory		 HW4
 
Week 6:
9/28 - 10/2

Midterm 1 (9/30, 7-9pm)

No class on Wednesday, 9/30

Properties of the DTFT
Frequency response

 Chapter 4: 4.3 - 4.5
Chapter 5: 5.1 - 5.2		 SM: 2.4, 5.1
OS: 2.8-2.9, 5.1
PM: 4.2-4.4
FK: 18, 19
DTFT Python Demo
Filtering Python Demo		 HW5
 
Week 7:
10/5 - 10/9		 Frequency response (magnitude and phase responses)
Ideal filters
Sampling of continuous-time signals		 Chapter 5: 5.3 - 5.6
Chapter 6: 6.1		 SM: 5.2, 3.2
OS: 5.3-5.4, 4.1-4.2
PM: 4.4-4.5, 1.4
FK: 20, 21		 HW6
 
Week 8:
10/12 - 10/16		 Ideal C/D and D/C conversion
Aliasing effect
Discrete Fourier transform (DFT)
 Chapter 6: 6.2 - 6.3
Chapter 7: 7.1 - 7.2		 SM: 3.2, 2.5
OS: 4.2-4.3
PM: 1.4, 4.2.9, 5.1
FK: 22, 34
Sampling Demo		 HW7
 
Week 9:
10/19 - 10/23

Quiz 2 Period

Discrete Fourier transform (DFT)
DFT spectral analysis
DFT applications

 Chapter 7: 7.2 - 7.4; 7.6
Chapter 6: 6.4-6.5		 SM: 2.5-2.6
OS: 8.1-8.6, 10.1-10.2
PM: 5.2, 5.4
FK: 34, 36
DFT Python Demo		 HW8
 
Week 10:
10/26 - 10/30		 Fast Fourier transform (FFT)
Convolution using the DFT
Digital processing of analog signals		 Chapter 7: 7.5
Chapter 8: 8.1; 8.3		 SM: Ch 14, 6.3
OS: 8.7, 9.3, 6.1-6.2
PM: 5.3, 6.1-6.2, 7.1
FK: 37, 38.		 HW9
 
Week 11:
11/2 - 11/6

Midterm 2 (11/4, 7-9pm)

No class on Wednesday, 11/4

Practical digital filters
FIR filter design

 Chapter 12: 12.1-12.2   HW10
 
Week 12:
11/9 - 11/13

Generalized linear phase filters
FIR filter design by windowing

 Chapter 9: 9.1-9.3
Chapter 10: 10.1-10.3
Chapter 11: 11.1; 11.3		 SM: 6.4, Ch 11, Ch 12
OS: 5.7, Ch 7
PM: Ch 8 
FK: 28, 29, 30.		 HW11
 
Week 13:
11/16 - 11/20

Downsampling and decimation
Upsampling and interpolation
Multirate signal processing

 Chapter 12: 12.1-12.2   HW12
 
Fall break:
11/23 - 11/27		        
Week 14:
11/30 - 12/4

Quiz 3 Period

Practical A/D, D/A, upsampling D/A, ZOH
Applications: instructor's choice, student's choice

 Chapter 6: 6.5
Chapter 15: 15.3		   HW13
 
Week 15: 12/7 - 12/11 Applications: instructor's choice, student's choice
Final exam review		  

 

 

  
Week 16: Final Exams: 12/14 - 12/18        

V. Grading and Exams

  1. Weekly Homework: 10% of Final Grade,
    • Grading: Homework average is computed by dropping the two lowest scores and then computing the average; this implies that each student may omit two homeworks in case of extenuating circumstances. Since the solutions will be posted immediately after the submission deadline, no late submission will be accepted.
    • Submission: Homework should be uploaded as a PDF file to Gradescope in which we have added each student enrolled. If you have not been auto-enrolled to our course Gradescope, you may join using entry code B4ED3K.
    • Due dates: Homework is assigned each Friday, due the following Friday at 11:59pm. The corresponding solution will be posted immediately after the due date.
    • Write neatly. Please box the equations you will be solving and the final answer. If we cannot read it we cannot grade it!
    • Regrade requests must be submitted on gradescope within one week of grades being posted. All regrade requests must have a brief justification.
    • Again, late homework submissions will not be accepted.
  2. Quizzes: 20% of Final Grade
    • There will be three (3) 50-minute quizzes given throughout the semester. Each quiz will serve as a checkpoint for students to assess their mastery of recent material leading into each of the midterms and the Final Exam.
    • The quizzes will be offered at the Computer-Based Testing Facility (CBTF) and students will be responsible to sign up for a time during each quiz period to take their quiz.
    • These quizzes will be held in Week 4, Week 9 and Week 14 of the semester.
    • Each quiz is worth 10% of the Final Grade.
    • We will drop your lowest quiz grade.
  3. Exams (will be held in-person): 70% of Final Grade
    1. Midterm Exam 1: 20% of Final Grade
      • Date: Wednesday, September 30th, 7-9pm
      • Location: To be announced
      • Coverage: material from weeks 1-4, through HW4.
      • You are allowed 1 sheet (two-sided) of handwritten notes (no printed notes) on 8.5x11" paper. No calculator allowed.
      • Conflict exam: To be announced
    2. Midterm Exam 2: 20% of Final Grade
      • Date: Wednesday, November 5th, 7-9pm
      • Location: To be announced
      • Coverage: materials corresponding to HWs 5-9.
      • You are allowed 1 sheet (two-sided) of handwritten notes (no printed notes) on 8.5x11" paper. No calculator allowed.
      • Conflict exam: To be announced
    3. Final Exam: 30% of Final Grade
      • Date: To be announced
      • Location: To be announced
      • Coverage: material from the whole semester
      • You are allowed 3 sheets (two-sided) of handwritten notes (no printed notes) on 8.5x11" paper. No calculator allowed
  4. Final Grade Cutoffs: The following cutoffs will be used to assess final grades. The cutoffs will never be raised, but might be lowered based on the class distribution. We will communicate any changes clearly in class and here on the website.
  • A+: 93-100, A: 90-93, A-: 87-90
  • B+: 83-87, B: 80-83, B-: 77-80
  • C+: 73-77, C: 70-73, C-: 67-70
  • D+: 63-67, D: 60-63, D-: 57-60

DRES Accommodations

We encourage students with DRES accommodations to take their Midterm Exams and Final Exam at the Testing Accommodations Center (TAC). Please list Prof. Snyder as your instructor for TAC (regardless of which section you are in) and share your letter of accommodation. If you have any additional concerns or preferences, please feel free to reach out to Prof. Snyder.

VI. Integrity and AI Usage

This course will operate under the following honor code: All exams and homework assignments are to be worked out independently. Copying of other students' work is considered cheating and will not be permitted. By enrolling in this course and submitting exams and homework assignments for grading, each student implicitly accepts this honor code.

Generative AI tools, such as ChatGPT, Microsoft Copilot, and Gemini, can answer questions and generate text, images, and other media. The appropriate use of generative AI varies from course to course. In ECE 310 there are times when generative AI may be useful in the course and other times where we prohibit the use of generative AI. Specifically, you MAY use generative AI in ECE 310 to aid your studying and preparation for exams, and to help verify your own solutions when completing homework assignments. This includes generating additional practice problems, verifying your solutions to other example problems, and checking your own understanding of course concepts. You MAY NOT use generative AI in ECE 310 on any quizzes or exams, or fully copy/plagiarize generative AI solutions on homework assignments. Solutions that are direct copies of answers from a Generative AI tool may be subject to disciplinary action such as a FAIR allegation.

If you have a question about the use of Generative AI, please feel free to reach out to Prof. Snyder.  Failure to abide by these guidelines is a violation of academic integrity. We will investigate suspected uses of generative AI that do not follow these guidelines and apply sanctions as outlined in the University of Illinois Student Code.

VII. Homework Material

Exercises Due Date Solution
Homework 1 09/04 @ 11:59pm Homework 1 Solution
Homework 2 09/11 @ 11:59pm Homework 2 Solution
Homework 3 09/18 @ 11:59pm Homework 3 Solution
Homework 4 09/25 @ 11:59pm Homework 4 Solution
Homework 5 10/04 @ 11:59pm Homework 5 Solution
Homework 6 10/09 @ 11:59pm Homework 6 Solution
Homework 7 10/16 @ 11:59pm Homework 7 Solution
Homework 8 10/23 @ 11:59pm Homework 8 Solution
Homework 9 10/30 @ 11:59pm Homework 9 Solution
Homework 10 11/08 @ 11:59pm Homework 10 Solution
Homework 11 11/13 @ 11:59pm Homework 11 Solution
Homework 12 11/20 @ 11:59pm Homework 12 Solution
Homework 13 12/19 @ 11:59pm Homework 13 Solution

VIII. Past Exams

Exam Exam List
Midterm 1 Coming Soon
Midterm 2 Coming Soon
Final Coming Soon