Signal Processing

A.Y. 2025/2026
12
Max ECTS
104
Overall hours
SSD
INF/01
Language
Italian
Learning objectives
The course is structured into two teaching units.
The aim of the first unit (6 CFU) is to teach the fundamental concepts of signal and system theory, focusing on continuous-time and discrete-time signals and systems (with specific reference to acoustic signals).
The second unit (6 CFU) aims at providing student with basic notions of digital audio signal processing.
Expected learning outcomes
At the end of the first unit, the student shall be able to: represent signals and systems both in the time domain and in the frequency domain; design continuous-time and discrete-time filters; correctly design an analog-to-digital signal conversion.
At the end of the second unit, the student shall be able to master the representations and the transformations of audio signal in the time domain and in the frequency domain, also by means of dedicated programming languages.
Single course

This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.

Course syllabus and organization

Single session

Responsible
Lesson period
First semester
Course syllabus
The class is composed of two modules.

The first module is dedicated to the fundamentals of signal theory and the basic concepts of analog and digital signal processing.
The main topics are:
- Elements of complex mathematics
- Signals and systems
- Frequency analysis: Fourier series and Fourier transform.
- Filtering of analog signals.
- Analog/digital conversion: sampling, quantization.
- Time-discrete Signals.
- Frequency analysis: of discrete signals: DTFT, DFT.
- The Z-transform.
- Digital filters.

For the second module, the program is focused on the following topics
- Introduction to audio signal processing using MATLAB
- Audio content analysis (signals, sampling, quantization, convolution, Fourier transforms, correlation)
- Audio Features (statistical, spectral, postprocessing, dimensionality)
- Short term audio processing (Signal Transforms and Filtering Essentials)
- Audio classifiers (speech, emotion, urban sounds, etc.)
Prerequisites for admission
Good knowledge of the topics taught in the Mathematics class in the first year, therefore having passed the Mathematics exam is compulsory.
Having passed the exam of Programming is also a compulsory requirement for this course. Moreover, having passed the exam of Acoustics is strongly recommended.
Teaching methods
Lectures and exercises
Teaching Resources
For the first module:
Web sites:
- https://pedersini.di.unimi.it/ES
- http://fpedersinies.ariel.ctu.unimi.it/v5/home/Default.aspx

Class material:
- course text: F. Pedersini - Elementi di segnali e sistemi - Amazon KDP (italian)
- A. Bertoni, G. Grossi - Dispense di Elaborazione Numerica dei Segnali (italian)
- Solved exercises and examples of written test

Reference textbook:
- J. G. Proakis, D. G. Manolakis - Digital Signal Processing - Pearson

For the second module:
Web site:
- https://sntalampirasias1.ariel.ctu.unimi.it/
- https://myariel.unimi.it/course/view.php?id=7384
Books:
- An Introduction to Audio Content Analysis: Applications in Signal Processing and Music Informatics, https://www.audiocontentanalysis.org/ https://dl.acm.org/doi/10.5555/2392638
- Audio and Speech Processing with MATLAB, https://www.routledge.com/Audio-and-Speech-Processing-with-MATLAB/Hill/p/book/9780367656317
- Introduction to Audio Analysis: A MATLAB Approach, https://www.elsevier.com/books/introduction-to-audio-analysis/giannakopoulos/978-0-08-099388-1
Additional materials:
- Matlab reference help
Assessment methods and Criteria
For the first module, the exam consists of a written test followed by oral test. Students are admitted to the oral test only if the written test obtained a positive evaluation. Both tests are aimed to assess the level of understanding of the taught arguments.

For the second module, the final exam consists of a written test and of the development of a project to be delivered to the teacher, with no oral discussion.
The evaluation is given in 30ths and is based on the following aspects: mastering of the course topics, ability to apply the acquired knowledge to solving actual problems, logical and critical thinking.
INF/01 - INFORMATICS - University credits: 12
Laboratories: 16 hours
Lessons: 88 hours