Signals and Systems introduces the foundational concepts of signal processing theory. This course focuses on applying linear systems theory and basic signal processing methods, crucial for analyzing various types of data.
- Understand and apply linear time-invariant (LTI) systems.
- Analyze signals in both time and frequency domains.
- Utilize Z and Laplace transforms.
- Design recursive and non-recursive filters.
- Apply Discrete and Fast Fourier Transforms (DFT and FFT).
- Analyze signals in noisy environments.
- Lectures: Tuesdays, 2 hours - Introduction of weekly study topic by the lecturer.
- Office Hours: Fridays, 2 hours - Q&A sessions focusing on lab assignments.
- Tutorials: Weekly, 2 hours (group-specific) - Exercises and AI use cases related to the weekly topic.
The course follows the outline below for weekly topics and readings:
| Week | Topic | Chapters in the Book |
|---|---|---|
| 46 | Signals and Systems | 1 |
| 46 | Sinusoids and Euler's Formula | 2 |
| 47 | Spectrum Representation | 3 |
| 48 | Sampling and Aliasing | 4 |
| 49 | FIR Filters and LTI Systems | 5 |
| 50 | Frequency Response of FIR Filters | 6 |
| 51 | Discrete-time Fourier Transform | 7, 8 |
| 2 | Z-Transform | 9 |
| 3 | Laplace Transform & Summary | - |
| 4 | Final Exam | - |
- Linear Time-Invariant Systems
- Time Domain and Time-Frequency Domain Analysis
- Z and Laplace Transform
- Filter Design (Recursive and Non-Recursive)
- Discrete Fourier Transform (DFT)
- Fast Fourier Transform (FFT)
- Spectra Analysis
- Signal Analysis in Noise
- McClellan, J. H., Schafer, R. W., & Yoder, M. A. (2016). Digital Signal Processing First. Pearson Education.
- Schafer, R. W., Yoder, M. A., & McClellan, J. H. (2003). Signal Processing First. Prentice Hall.
- Oppenheim, A., Willsky, A., & Nawab, S. (1997). Signals and Systems. Pearson Education.
- Brunton, S. L., & Kutz, J. N. (2022). Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control. Cambridge University Press.
- Prandoni, P., & Vetterli, M. (2008). Signal Processing for Communications. EPFL Press.
- Lab Assignments (25%)
Submission: Code through Themis and documentation on Brightspace. Working in pairs is recommended. - Final Exam (75%)
Covers all lectures and tutorials. Minimum grade requirement: both assignments and exams must be at least 5 to pass.
- Deductions: 1 point for every 24 hours late, up to 3 days.
- After 72 Hours: Late component is marked zero.
Each lab has two components:
- Code (70%) - Weekly problem solutions.
- Documentation (30%) - Selected problem explanations.
Submit code via Themis and documentation on Brightspace.
Students are expected to use personal laptops. For those without access, Chromebooks can be borrowed from the Student Administration Desk (Bernoulliborg, first floor) during open hours.
Use of generative AI tools is allowed within the UG guidelines. AI assistance should be used responsibly, avoiding overgeneralizations, redundancies, or misalignments with course content.
Further details on UG AI policy.
Signals and Systems supports other AI courses by building foundational skills in signal processing. This knowledge is crucial for tasks like denoising, compression, and feature extraction, aiding in the interpretation of complex data.