Digital Signal Processing (IF3024)
Course Schedule:
Tuesday, 7.30 - 10.00 WIB
Important links:
About The Course
Description
This course explores the techniques and methods of processing and analyzing digital signals. Students will learn the fundamental concepts of digital signals, signal transformation, and digital signal processing techniques. Additionally, the course covers the implementation of digital signals in various applications, including audio, video, and image processing.
Learning Outcomes
- Students are able to understand the basic concepts of digital signal processing
- Students are able to demonstrate basic mathematical concepts related to digital signal processing
- Students are able to apply basic processing techniques to common problems related to digital signal
- Students are able to design a digital signal processing system to solve a specific problem
Grade Distribution and Scale
A: >= 75 | AB: 70 - 74 | B: 65 - 69 | BC: 60 - 64 | C: 50 - 59 | D: 40 - 49 | E: < 40
Rounding: 0 decimal, 0.5 and above rounded up
- Class Participation: 15%
- Hands-on Assignment: 40%
- Midterm Exam: 10%
- Final Project: 35%
Class Regulation
Please refers to this: kontrak kuliah
References
- Richard G. Lyons and D. Lee Fugal. The Essential Guide to Digital Signal Processing. Prentice Hall, Englewood Cliffs, New Jersey, 2014.
- James D. Broesch. Digital Signal Processing–Instant Access. Newnes, Burlington, MA, 2009.
Schedule and Materials
| Week | Topics | Assignments / Grading | Resources |
|---|---|---|---|
| 1 | Course Logistics Introduction to Digital Signal Processing |
1. IDE Setup 2. How ANC Works - YT 3. ADC 4. Signal Visualization |
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| 2 | Discrete Time System | ||
| 3,4 | Working with Python for Digital Signal Processing Sinusoids and Basic Signals 1. Sinusoids 2. Sampling 3. Aliasing 4. Basic Signal and Filters |
How do Complex Numbers relate to Real Signals? - Youtube | |
| 5,6,7 | LTI Systems and Time Domain Analysis 1. LTI Systems Intro 2. Time Invariance Examples 3. Impulse Response |
||
| 8 | Mid-Term Week | ||
| 9 | Discrete Fourier Transform (DFT) | 1. Wavelet Transform 2. DFT |
|
| 10,11 | Frequency Domain 1. Frequency Domain Analysis 2. Harmonics 3. Discrete Fourier Transform 4. Frequency Response 5. Spectogram |
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| 12,13 | Digital Filter | ||
| 14,15 | Case Study: Measuring Respiration Signal from Video | ||
| 16 | Final Project Presentation |
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