https://github.com/glassnotes/signals-and-systems-oer-labs

Hands-on Python activities for undergraduate signals and systems courses.
https://github.com/glassnotes/signals-and-systems-oer-labs

Last synced: about 2 months ago
JSON representation

Hands-on Python activities for undergraduate signals and systems courses.

• Host: GitHub
• URL: https://github.com/glassnotes/signals-and-systems-oer-labs
• Owner: glassnotes
• License: cc0-1.0
• Created: 2024-01-06T19:13:36.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-04-30T19:19:26.000Z (8 months ago)
• Last Synced: 2024-04-30T20:32:47.186Z (8 months ago)
• Language: Jupyter Notebook
• Size: 19.8 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11094778.svg)](https://doi.org/10.5281/zenodo.11094778)

# Signals and Systems OER Labs

This repository contains a set of hands-on, guided Jupyter notebooks that we developed to teach undergraduate students topics in signals and systems for ELEC 221 at UBC.

Development of these materials was financially supported by the UBC [Open Educational Resource (OER)](https://oerfund.open.ubc.ca/) Fund Implementation Grant in 2023-24. The material was 

developed primarily by UBC undergraduate students

 * Sofiya Spolitak ([@SofiyaSp](https://github.com/SofiyaSp))

 * Sidharth Sudhir ([@sidharthsudhir-03](https://github.com/sidharthsudhir-03))

under the supervision of Profs. Olivia Di Matteo ([@glassnotes](https://github.com/glassnotes/)) and

Christos Thramboulidis ([@cthrampo](https://github.com/cthrampo)).

## Contents

This repository contains 9 hands-on labs based on a variety of topics. Learning outcomes can be found at the top of each Jupyter notebook.

 1. Introductory materials (Python, NumPy, Jupyter notebooks)

 2. Audio processing with Fourier analysis and filters (building a simple sound equalizer)

 3. Image processing (filters and effects in airport scanners)

 4. Video processing (filtering and compression in video games)

 5. Data and discrete-time signals (analyzing trends in COVID data)

 6. Up/downsampling and multiplexing (building a simulated radio)

 7. Communication systems (decoding satellite communications)

 8. Amplitude modulation (synthesizing sounds with the Karplus-Strong algorithm)

 9. Laplace transforms and control systems (building a self-regulating thermostat)

## Sharing and contributing

These materials are made available under the CC-0 v1.0 License.

If you use or extend these labs for your own courses, we would love to see - please get in touch!

If you find any errors, please open an issue in the repository.

## Acknowledgments

We thank UBC's OER Fund Implementation Grant for financial support, and the students in the Fall 2023 cohort of ELEC 221 for their feedback on the first run of the new labs.

ODM thanks the students in the Fall 2022 cohort of ELEC 221 for their enthusiasm and feedback on the initial versions of some of the materials, in particular Simon Ghyselincks ([@chipnbits](https://github.com/chipnbits)) for uncovering some kinks in the simulated AM radio.

CT expresses gratitude for the valuable suggestions and assistance provided by [Yekaterina Kharitonova](https://cs.ucsb.edu/index.php/people/faculty/yekaterina-kate-kharitonova) in the preparation of the Intro Lab (Python Crash Course).