Signal Processing
A.Y. 2024/2025
Learning objectives
The aim of the course 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 course focuses in particular on: signal and system representations in time- and frequency-domain, signal processing (filtering), and analog/digital signal conversions.
Expected learning outcomes
At the end of the course, 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.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
The class 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.
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.
Prerequisites for admission
Good knowledge of the topics taught in the Mathematics class in the first year.
Teaching methods
Lectures and exercises
Teaching Resources
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
- 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
Assessment methods and Criteria
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.
INF/01 - INFORMATICS - University credits: 6
Practicals: 12 hours
Laboratories: 16 hours
Lessons: 32 hours
Laboratories: 16 hours
Lessons: 32 hours
Professor:
Pedersini Federico
Shifts:
Turno
Professor:
Pedersini FedericoProfessor(s)