Digital Signal Processing Applications

EE482 Spring 2022


Description

Professor

Dr. Brendan Morris,
Office: SEB 3216
OH: TBD

Lecture

Lecture: MoWe 16:00-17:15, TBE B-176
Final: M May 09, 18:00-20:00
Look up your final exam schedule now to determine conflicts.

Textbook:
Real-Time Digital Signal Processing: Fundamentals, Implementations, and Applications, 3rd Edition, Kuo, Lee, Tian, ISBN: 978-1-118-41432-3
Recommended Text:
The Scientist and Engineer's Guide to Digital Signal Processing, Smith, ISBN: 978-0966017632.
Available Free Online http://www.dspguide.com/pdfbook.htm
Recommended IP/CV Texts:
Digital Image Processing, 3rd Edition, Gonzalez and Woods, ISBN: 978031687288.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools and Techniques to Build Intelligent Systems, 2nd Edition, Geron, ISBN: 9781492032649. Image Processing, Analysis, and Machine Vision, 4th Edition, Sonka, Hlavac, and Boyle, ISBN: 978-1-133-59360-7 Available online [link]
Computer Vision: Algorithms and Applications, Richard Szeliski. Available online [link]



Catalog Description:
Application of signals and systems theory. Topics may include audio and speech signal processing, image processing, multi-spectral imaging, biomedical signals, and active sensing technologies such as Radar and Lidar.
Prerequisites: EE361

NOTE: This information will evolve.

The information below is a reference based on previous iterations of the course. This semester will be geared toward the 1/10 scale autonomous vehicle design from the 2022 BFMC

The 2022 Bosch Future Mobility Challenge (BFMC) is an international (Cluj, Romania) technical student competition to develop a 1:10 scale model car kit to develop an autonomous vehicle (navigate stop/light controlled intersections, avoid pedestrians, pass vehicles, park, etc.) The key components of the competition include: Important dates: Course Syllabus: [pdf]

Grading

ComponentPercentageDate
Final: 20% 05/09 18:00
Quizzes (5): 25% TBD
Project: 25% 05/08
Homework: 30% Bi-Weekly
Homework will include Matlab programming problems. Students may work together in study groups but all assignments must be completed individually. Homework will be due in class on the designated date. No late homework will be accepted unless prior notification and arrangements are made. The course will have a term project. You will be required to submit a project report in the form of a conference styled manuscript and make a presentation.

Gradebook

The gradebook is available through UNLV Webcampus [link].
Note that the calculated % is not necessarily reflective of your final grade. The gradebook should be used mainly to ensure that I have correctly recorded your scores.

Announcements

DateNote
01/17/22 Welcome to Spring 2022. Please note we start the class on Wed 1/19. The course topics and schedule will be updated as we move through the course but will be geared toward developing a 1:10 scale car for the BFMC.

Schedule (Tentative)

WeekDateLecture TopicReadingAssignment
1 01/17 Mo MLK Holiday - course intro [pdf] RTDSP Ch 1 [pdf] HW01 [pdf]
Due F 02/04
Solutions [pdf]
01/19 We Real-Time DSP Introduction [Ch1.0-1.3][pdf]
2 01/24 Mo DSP Fundamentals [WebEx][Ch2.0-2.2] [pdf] RTDSP Ch 2 [pdf] HW02 [pdf]
Due F 02/11
Solutions [pdf]
01/26 We Random variables and Numerical effects [WebEx][Ch2.3-2.5][pdf]
3 01/31 Mo FIR Filter Design and Implementation [WebEx][Ch3][pdf] RTDSP Ch 3 [pdf]
02/02 We FIR Filter Design and Implementation [WebEx]
4 02/07 Mo IIR Filter Design and Implementation [WebEx][Ch4.1-4.2] RTDSP Ch 4 [pdf] HW03 [pdf]
Due F 02/18 02/25
Solutions [pdf]
02/09 We IIR Filter Design [WebEx][Ch4.3-4.6]
5 02/14 Mo Quiz01 Review [WebEx]
02/16 We Quiz01 Ch1-3 [pdf]
6 02/21 Mo President's Day - Image Processing [Ch11] RTDSP Ch 11 [v0] HW04 [pdf]
Due F 03/04
Solutions [pdf]
02/23 We Image Processing [WebEx]
7 02/28 Mo Image Processing [WebEx]
03/02 We Frequency Filtering [WebEx][pdf]
8 03/07 Mo Object Recognition [WebEx][pdf] Viola and Jones [pdf]
03/09 We Quiz 02 [WebEx]
9 03/14 Mo Spring Break
03/16 We Spring Break
10 03/21 Mo Project Introduction [pdf]
Object Detection [WebEx][pdf]
Szeliski Ch6
03/23 We Object Detection [WebEx]
11 03/28 Mo Object Detection [WebEx] Geron Ch14 HW05 [pdf]
Due F 04/15
03/30 We Deep Object Detection [WebEx][pdf]
12 04/04 Mo Deep Object Detection [WebEx] Zhao Object Detection Review [pdf]
04/06 We Quiz 03 Image Processing [WebEx]
13 04/11 Mo Deep Object Detection [WebEx] Geron Ch1, 10
04/13 We Overview ML + NN [WebEx][pdf]
14 04/18 Mo Quiz 04 Detection [WebEx] HW06 [pdf]
Due M 04/25 W 04/27
04/20 We Project Review [WebEx]
15 04/25 Mo Project Review
04/27 We Quiz 05 Deep Detection
16 05/02 Mo Project Presentations
05/04 We Project Presentations
17 05/09 Mo Final -