Time & Location: MW 4:30–5:45 PM, In-Person @ 1231 EB2 or Online Synchronous (Zoom link can be found on Piazza)
Instructor: Dr. Chau-Wai Wong
Teaching Assistants: Fin Amin & Gavin Carter
Discussion Forum: ECE 301 on Piazza
Homework submission (due at 4:30 PM before class): Gradescope (for the first time, log in Gradescope via Moodle.)
Office hours: Wong on Wednesdays 11 AM–12 PM; Fin on Mondays 3–4 PM; Gavin on Tuesdays 1–2 PM
Course Description: This course covers the fundamental concepts in signal processing, with a focus on linear time-invariant systems. Signal processing has found its applications in many disciplines such as communications, controls, machine learning, bioengineering, security/privacy, and circuits. Having a good grasp of both intuitions and mathematics of signal processing theories can greatly benefit a student’s future role as an engineer.
Topics: Characterization of continuous- and discrete-time systems, sampling theorem, Fourier transforms, Laplace transform, and z-transform. In the Spring 2022 offering, we will also cover basic machine learning tools such as the principal component analysis (PCA), the linear regression, and the convolutional neural network (CNN).
Prerequisites: ECE 211 and ECE 220.
Followup ECE courses: 421 (Signal Processing); 402 (Communications); 407 & 470 (Computer Networking); 308 & 436 (Controls); 456 (Mechatronics); 451 (Power System); 411 (Machine Learning)
Course structure & Grading: The course consists of two 75-minute in-person lectures per week. Alternatively, you may attend the lectures online via Zoom. There will be weekly homework assignments (40%) that contains both written problems and programming problems, two midterm exams (2*20%), and one final exam/project (20%). Programming will be in Matlab, and optionally, in Python or R.
Textbooks: [OW] A. V. Oppenheim and A. S. Willsky, Signals and Systems, Prentice Hall, 2nd edition.
Reference Books:Some scanned sections/chapters of the books listed above can be found at NC State Course Reserves.
| Class # | Date | Topic | Lecture notes | Videos | Meeting time | Reading Assignment | HW Assignment | |
| 1 | 1/10 | Intro, Math review | Slides Ch0 | Zoom | 4:30 pm | VT 1.2.3–4 | ||
| 2 | 1/12 | Math review (cont'd) | Zoom | 4:30 pm | VT Ch4, 1.5.2, 1.6, 1.8 | HW1 (due 1/19) | ||
| 1/17 | MLK holiday (no class) | |||||||
| 3 | 1/19 | CT & DT signals; Complex exp | Slides Ch1 | Zoom | 4:30 pm | OW 1.1–4 | HW2 (due 1/26) | |
| 4 | 1/24 | Impulse & step functions | Zoom | 4:30 pm | OW 1.1–4 | |||
| 5 | 1/26 | System examples & simple system properties | Zoom | 4:30 pm | OW 1.5–6 | HW3 (due 2/2) | ||
| 6 | 1/31 | Time-invariance, linearity | Zoom | 4:30 pm | OW 1.6 | |||
| 7 | 2/2 | DT system response, DT convolution | Slides Ch2A | Zoom | 4:30 pm | OW 2.1–2 | HW4 (due 2/9) | |
| 8 | 2/7 | DT & CT convolution | Zoom | 4:30 pm | OW 2.2 | |||
| 9 | 2/9 | CT convolution (cont'd) | Zoom | 4:30 pm | HW5 (due 2/16) | |||
| 10 | 2/14 | LTI properties | Slides Ch2B | Zoom | 4:30 pm | OW 2.3 | ||
| 11 | 2/16 | Q&A; Linear algebra review | Slides ML | Zoom | 4:30 pm | VT Ch5–6; Scheffe App 1 |
No HW | |
| 12 | 2/21 | Q&A; Vector space | Zoom | 4:30 pm | ISLR 10.2, Murphy 12.2 |
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| 13 | 2/23 | Midterm 1 (exam paper) | 4:30 pm | HW6 (due 3/2) | ||||
| 14 | 2/28 | Q&A; Eigenanalysis | Zoom | 4:30 pm | Scheffe Ch1 | |||
| 15 | 3/2 | Principal component analysis (PCA) | Zoom | 4:30 pm | HW7 (due 3/9) Matlab code yalefaces.zip |
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| 16 | 3/7 | Linear regression | Zoom | 4:30 pm | DL Ch9 | |||
| 17 | 3/9 | Convolutional neural network (CNN) | Zoom | 4:30 pm | HW8 (due 3/24) | |||
| Spring break | ||||||||
| 18 | 3/21 | Fourier transform | Slides CTFT | Zoom | 4:30 pm | OW 4.1–2 (OW 3.2–4) |
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| 19 | 3/23 | Sinc, rect, and properties | Zoom | 4:30 pm | OW 4.2–3 | HW9 (due 3/31) | ||
| 20 | 3/28 | Convolution and multiplication | Zoom | 4:30 pm | OW 4.4–5 | |||
| 21 | 3/30 | DTFT and its properties | Slides DTFT | Zoom | 4:30 pm | OW 5.1-6 | HW10 (due 4/7) | |
| 22 | 4/4 | DFT; Relations among CTFT, DTFT, DFT | Slides DFT | Zoom | 4:30 pm | Johnson 5.7-9 | Final Exam/Project Dataset Interim report due 4/18 Final report due 5/4 |
|
| 23 | 4/6 | Sampling theorem, Nyquist frequency | Zoom | 4:30 pm | OW 7.1-3 | |||
| 24 | 4/11 | Midterm 2 (exam paper) | 4:30 pm | |||||
| 25 | 4/13 | Nyquist frequency (cont'd) | Zoom | 4:30 pm | ||||
| 26 | 4/18 | Bilateral Laplace transform, pole-zero plots, ROC | Slides Laplace | Zoom | 4:30 pm | OW 9.1-3 | ClassEval (bonus, due 4/26) |
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| 27 | 4/20 | CT LTI system characterization, connections to freq. response | Zoom | 4:30 pm | OW 9.4, 7, 8 | |||
| 28 | 4/25 | Z-transform, pole-zero plots, ROC DT LTI system characterization, connections to freq. response |
Slides z-Transform | Prerecorded on Pizza |
4:30 pm | OW 10.1-2 10.4-5 |