/IST-SElec-Labs

This repository contains lab materials for the IST-SElec course.

Primary LanguagePython

IST-SElec-Labs

This repository contains lab materials for the IST-SElec (Electronic Systems) course.

Content

This project focuses on studying the consequences of negative feedback in amplifiers, exploring configurations with and without feedback to illuminate the impacts on system behavior.

Learning Objectives

  • Understand the role of feedback in electronic systems and its implications on system performance.
  • Analyze amplifier configurations to observe the effects of feedback mechanisms.
  • Use LTspice® for simulation and MATLAB® for data analysis.

Technologies

  • LTspice® for circuit simulation.
  • MATLAB® for data processing and simulation analysis.

Topics Covered

  • Dessensitization of gain due to feedback.
  • Reduction of non-linear distortion and noise.
  • Control over input and output resistances.
  • Bandwidth enhancement of amplifiers.

Analyze a proximity detection system based on the principles similar to the Park-Aid circuit, which aids in vehicle parking by detecting nearby obstacles using sensors.

Learning Objectives

  • Dissect and study the individual components of the proximity detection circuit, including IR emitter and receiver, band-pass filter, rectifier with filtering, and proximity indicator.
  • Evaluate the circuit's performance and functionality as a whole.

Technologies

  • LTspice® for circuit simulation.
  • MATLAB® for data processing and simulation analysis.

Topics Covered

  • Oscillators and their applications in generating periodic signals.
  • Analog filters, including active and passive filters for signal processing.

The μOscilloscope project aims to design a small oscilloscope as an embedded system for IoT solutions development. The project encompasses understanding the hardware circuit, implementing oscilloscope software, debugging, optimizing, and calibrating the system.

Learning Objectives

  • Master the underlying hardware circuitry for the project.
  • Develop and implement the μOscilloscope software.
  • Perform debugging and software optimization.
  • Carry out calibration of the μOscilloscope.

Technologies

  • Software implementation compatible with Python 3 and MicroPython®, optimized for microcontrollers.
  • MATLAB® for data processing and simulation analysis.

Topics Covered

  • Implementation and calibration of oscilloscope software.
  • Signal processing algorithms and concepts.

Diagrams and Design Tools

All diagrams in this repository were created using draw.io, with the use of the ECE library provided by NicklasVraa/Draw-io-ECE. This tool and library facilitated the detailed depiction of electronic components and systems while offering a user-friendly and time-efficient design experience.

License

This work is licensed under a Creative Commons Attribution Non Commercial Share Alike 4.0 International.

Authors

Contributing

If you have suggestions or find any issues, please open an issue or submit a pull request.