Signals and Systems with Python

This course provides an introduction to signal theory and to how to model the relation between the input and output of systems. Topics covered:

- Fundamental signals and operations with signals (scaling, shifting, etc).

- Concepts of Energy and Power.

- Frequency domain representation of signals and the transformation and relation between the time and the frequency domain.

- Types of systems (causal vs non-causal, linear vs non-linear, time-invariant).

- Characterization of Liniear Time Invariant (LTI) systems by their impulse and frequency response, and the relation between input and output in time and frequency domains.

- Periodic signals and Fourier series.

- Fourier transform and its application to signals and systems.

- The Discrete Fourier Transform (DFT) and its applications to spectral analysis.

- Basic filters.

In addition, during this course students will be introduced to data analysis and signal-processing oriented programming using Python.