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.

The evaluation consists of a non-mandatory midterm, a mandatory final exam, and a pass/fail component for a set of quizzes and practical sessions. If the midterm score M is higher than the final exam score E and E is at least equal to 5.0 then the final grade is equal to 0.33 M + 0.67 E (rounded in the usual way), otherwise the final grade E is equal to E.

The rule only applies to Q2 in the year or years that the student takes the midterm. In other words, midterm grades from one academic year cannot be combined with the grade of the resit or the final grade of a different academic year.

Python has a weight of 40% in both the midterm and the final exam. Theory has a weight of 60% in both exams.

Permitted Materials during Exam: For the theory exams students can bring a maximum of five double-sided pages with notes or examples.

For more information on grading, see article 14 in the Rules and Guidelines (RGBE):
https://www.tudelft.nl/en/student/ceg-student-portal/education/education-information/educational-rules-and-regulations