SIGNALS AND SYSTEMS
cod. 1010003

Academic year 2022/23
2° year of course - First semester
Professor
Armando VANNUCCI
Academic discipline
Telecomunicazioni (ING-INF/03)
Field
Ingegneria delle telecomunicazioni
Type of training activity
Characterising
48 hours
of face-to-face activities
6 credits
hub: PARMA
course unit
in ITALIAN

Learning objectives

This course aims at introducing and developing the concepts of deterministic signal and random signal, as models for physical systems of interest in the engineering contexts (electronics, computer science, telecommunications and related subjects). Signal transfomrations are introduced, as models of various systems encountered in several areas of ICT (amplifiers, filters, transmission lines, modulators, samplers, etc.).
At the end of the course, the Student should:
- know the techniques for the analysis of signals in the frequency domain;
- being able to apply these techniques to the filtering an sampling of an analog signal;
- know and be able to communicate concepts related to random signal (mean parameters; power spectral density, stationarity,).
- be able to face the face and deepen autonomously the case-study of specific random processes (harmonic process, PAM signal, etc.).

Prerequisites

Knowledge of the fundamentals of Claculus, with specific reference to the algebra of complex numbers and their representation in the exponential form (and related Euler's forulae).
Detailed knowledge of the Theory of Probability, from elementary probability to random variables (RVs) and their moments, up to the characterization of couples of RVs and random vectors,.

Course unit content

In the first and largest part of this course (covering almost three quarters of it), we introduce deterministic signals and their analysis, both in the time- and in the frequency-domain. We shall analyze the trasformations that signals undergo through linear systems and through the sampling process;
The last part of the course exploits the previous knowledge about the theory of probability (studied in the first year). We introduce the concept of stochastic process, as a model to study random signals and their transformations throgh systems.

Full programme

- - -

Bibliography

- A. Vannucci, "Segnali analogici e sistemi ineari", Pitagora Editrice, Bologna, 2003, ISBN: 88-371-1416-8.
- A. Vannucci, "Esercizi d'esame di Teoria dei Segnali", Pitagora Editrice, Bologna, 2018, ISBN: 88-371-1811-2.

Teaching methods

This is a 6 credits (CFU) course, for which 48 hours of Class Lecturesare foreseen, to build up the understanding and critical processing of the subject matter.
Applications and exercises related to the presented topics are regularly proposed (via traditional or flipped classroom techniques) to develop application skills. Other assignments are given through the web learning platform Elly.
When foreseen by the long-term teaching plan of this University, a Tutor shall give guided exercises.
Teaching methods shall be adapted to the possible presence (detected according to laws and guidelines) of students with special needs and or disabilities.

COVID-19 WARNING:
- this course is held in presence and its lectures will NOT be recorded. Therefore:
a) no recordering s of the lectures will be available for off-line viewing;
b) no lecture shall be given to physically present students and on-line remote students at the same time: this a discouraged hybrid and uneffective teaching method, often and inappropriately called 'blended' by italians.
- students that do not have the possibility to attend the lectures (including those in the following conditions: quarantine; isolation due to Covid; exempt from vaccination due to physical fragility) are invited to contact the Instructor via email to illustrate and justify their non-attending student status. The Instructor shall provide those individual students with recording of the lectures by Prof. G. Prati (UniPR, Consorzio Nettuno) per personal viewing and studying.
- in the absence of necessary safety conditions related to the pandemic, the two "intermediate written tests" (see section on exams) shall be abolished, thus accessing directly the exam sessions in january.

Assessment methods and criteria

The overall assessment of the learning outcomes foresees two tests:
1) a structured written test with 2 open questions, where the student shall demonstrate his/her ability to:
- analyze an analog signal and its possible transformations, in the time and frequency domain;
- analyze a random signal and its possible filtering, by evaluating its moments and/or power spectrum
The duration of the written test is 1.5 hours. The test is evaluated on a 0-30 scale, plus possible honors, in the case of top grades in all items together with an ppropriateness of language.
2) an oral test, consisting of a critical discussion about the topics developed during the course. The student shall demonstrate proper knowledge and ability to illustrate the topic, with sufficient accuracy in the language.

Students can optionally take two intermediate written tests- to take place halfway during the course and at the end of the course, respectively - that shall replace the overall assessment procedure above.
The first test is a sequence of 10 closed multiple choice questions (whose only purpose is to grant access to the following step, if at least 6/10 of the answers are correct, hence the evaluation of this test has no impact on the final grade), followed by two open questions, similar to those illustrated at point 1) above.
The second test is is ismply made up of two open questions, similar to those illustrated at point 1) above.
In case the student takes both intermediate tests, the overall evaluation shall be assessed without an oral test.

Assessment methods shall be adapted to the possible presence (detected according to laws and guidelines) of students with special needs and or disabilities.

Other information

- - -

2030 agenda goals for sustainable development

- - -

Contacts

Toll-free number

800 904 084

Student registry office

E. segreteria.ingarc@unipr.it

Quality assurance office

Education manager:
Elena Roncai
T. +39 0521 903663
Office E. dia.didattica@unipr.it
Manager E. elena.roncai@unipr.it

 

President of the degree course

Gianluigi Ferrari
E. gianluigi.ferrari@unipr.it

Faculty advisor

Giovanna Sozzi
E. giovanna.sozzi@unipr.it

Career guidance delegate

Guido Matrella
E. guido.matrella@unipr.it

Tutor professor

Boni Andrea
E. andrea.boni@unipr.it
Caselli Stefano
E. stefano.caselli@unipr.it
Cucinotta Annamaria
E. annamaria.cucinotta@unipr.it
Nicola Delmonte
E. nicola.delmonte@unipr.it
Mucci Domenico
E. domenico.mucci@unipr.it
Saracco Alberto
E. alberto.saracco@unipr.it
Ugolini Alessandro
E. alessandro.ugolini@unipr.it
Vannucci Armando
E. armando.vannucci@unipr.it

Erasmus delegates

Paolo Cova
E. paolo.cova@unipr.it
Corrado Guarino
E. corrado.guarinolobianco@unipr.it
Walter Belardi
E. walter.belardi@unipr.it

Quality assurance manager

Massimo Bertozzi
E. massimo.bertozzi@unipr.it

Tutor students

SPAGGIARI Davide E. davide.spaggiari@unipr.it
MUSETTI Alex E. alex.musetti@unipr.it
BERNUZZI Vittorio E. vittorio.bernuzzi1@studenti.unipr.it
NKEMBI Armel Asongu E. armelasongu.nkembi@unipr.it
BASSANI Marco E. marco.bassani@unipr.it
ZANIBONI Thomas E. thomas.zaniboni@unipr.it
BOCCACCINI Riccardo E. riccardo.boccaccini@unipr.it
MORINI Marco E. marco.morini@unipr.it
SHOZIB Md Sazzadul Islam E. mdsazzadulislam.shozib@studenti.unipr.it