Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technicaladministrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period  From  To 

I semestre  Oct 1, 2019  Jan 31, 2020 
II semestre  Mar 2, 2020  Jun 12, 2020 
Session  From  To 

Sessione invernale d'esame  Feb 3, 2020  Feb 28, 2020 
Sessione estiva d'esame  Jun 15, 2020  Jul 31, 2020 
Sessione autunnale d'esame  Sep 1, 2020  Sep 30, 2020 
Session  From  To 

Sessione Estiva  Jul 15, 2020  Jul 15, 2020 
Sessione Autunnale  Oct 16, 2020  Oct 16, 2020 
Sessione Autunnale Dicembre  Dec 11, 2020  Dec 11, 2020 
Sessione Invernale  Mar 17, 2021  Mar 17, 2021 
Period  From  To 

Festa di Ognissanti  Nov 1, 2019  Nov 1, 2019 
Festa dell'Immacolata  Dec 8, 2019  Dec 8, 2019 
Vacanze di Natale  Dec 23, 2019  Jan 6, 2020 
Vacanze di Pasqua  Apr 10, 2020  Apr 14, 2020 
Festa della Liberazione  Apr 25, 2020  Apr 25, 2020 
Festa del lavoro  May 1, 2020  May 1, 2020 
Festa del Santo Patrono  May 21, 2020  May 21, 2020 
Festa della Repubblica  Jun 2, 2020  Jun 2, 2020 
Vacanze estive  Aug 10, 2020  Aug 23, 2020 
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.
Academic staff
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
Modules  Credits  TAF  SSD 

Mathematical analysis 1
Computer Architecture
2° Year activated in the A.Y. 2020/2021
Modules  Credits  TAF  SSD 

3° Year activated in the A.Y. 2021/2022
Modules  Credits  TAF  SSD 

Modules  Credits  TAF  SSD 

Mathematical analysis 1
Computer Architecture
Modules  Credits  TAF  SSD 

Modules  Credits  TAF  SSD 

Legend  Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
System theory (2020/2021)
Teaching code
4S02785
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
INGINF/04  SYSTEMS AND CONTROL ENGINEERING
The teaching is organized as follows:
Laboratorio
Teoria
Learning outcomes
The course objective is to give students the mathematical tools required for the analysis and modeling of linear, timeinvariant (LTI) systems, and of the input/output signals to an LTI system. The model will allow students to study the main system properties and to address the general concepts of controller and filters to perform simple control actions on the dynamic system and filter operations on the input/output signals. The mathematical tools will be based on analysis methods in the time domain, as well as of the complex variables s, z and the frequency of the input/output signals. Analysis and synthesis will be carried out both for continuous and discrete time systems and signals. The theoretical concepts acquired during the course will be consolidated with exercise sessions addressing the solution of basic problems with analytical approach and with numerical simulations.
Program
1. Review: complex numbers, functions of complex variables, series of complex powers, convergence, Euler's formula
2. Distributions: impulse, step, ramp. Sampling and reproducibility. Sinusoidal exponential functions, time translation. Discrete signals
3. Continuous time systems. Causal LTI systems. Stability.
4. Characteristic equation of a system, elementary modes, convergence.
5. Convolution, impulsive response, forced response, BIBO stability, asymptotic stability
6. Frequency response
7. The Laplace transform. Convergence region. Properties
8. Free response and forced response in the complex plane, transfer function, zeros and poles, stability.
9. The Laplace's antitrasform, poles, residues.
10. The Fourier series for periodic signals. Frequency, pulsation, linear combination of periodic signals, synthesis equation, analysis equation. The energy and power of a signal, the discrete spectrum.
11. The Fourier transform. Conditions of existence, discontinuities.
12. Convolution and modulation. Spectrum.
13. Fourier trasform of the ideal sampling train, replication and sampling, reconstruction filters, Nyquist frequency, Shannon forumula.
14. Bode diagrams
15. Block diagrams
16. Discretetime LTI systems. ARMA model. Impulsive response, forced response.
16. z trasform. Properties
17. The antitransformed z. Frequency response. Discrete Fourier transform
The students can integrate the reference books ('Segnali e Sistemi' by M.E. Valcher and 'Regolazione Automatica' by Di Stefano et al. for the laboratory part) with the free text at the link:
https://ptolemy.berkeley.edu/books/leevaraiya/
On moodle elearning website there is the complete material of both theory and exercises. There will be also a laboratory part that consists in MatlabSimulink implementation.
Office hours: after class
Bibliography
Activity  Author  Title  Publishing house  Year  ISBN  Notes 

Teoria  Dalle lezioni  Appunti dalle lezioni  2021  
Teoria  M.E. Valcher  Segnali e Sistemi  Ediitrice Progresso  2002 
Examination Methods
The exam is written and oral. Only those who pass the written exam may access the oral examination.
Type D and Type F activities
years  Modules  TAF  Teacher 

3°  The fashion lab (1 ECTS)  D 
Maria Caterina Baruffi
(Coordinator)

years  Modules  TAF  Teacher 

3°  Control theory  D 
Riccardo Muradore
(Coordinator)

3°  Biomedical Data and Signal Processing  D 
Silvia Francesca Storti
(Coordinator)

3°  Python programming language  D 
Maurizio Boscaini
(Coordinator)

years  Modules  TAF  Teacher 

3°  CyberPhysical Laboratory  D 
Andrea Calanca
(Coordinator)

3°  C++ Programming Language  D 
Federico Busato
(Coordinator)

3°  LaTeX Language  D 
Enrico Gregorio
(Coordinator)

3°  MatlabSimulink programming  D 
Bogdan Mihai Maris
(Coordinator)

years  Modules  TAF  Teacher 

3°  Corso Europrogettazione  D  Not yet assigned 
3°  The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka.  D 
Matteo Cristani

Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.
Graduation
List of thesis proposals
theses proposals  Research area 

Analisi e percezione dei segnali biometrici per l'interazione con robot  AI, Robotics & Automatic Control  AI, Robotics & Automatic Control 
Integrazione del simulatore del robot Nao con Oculus Rift  AI, Robotics & Automatic Control  AI, Robotics & Automatic Control 
Domain Adaptation  Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems  Computer graphics, computer vision, multi media, computer games 
Domain Adaptation  Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems  Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video) 
BS or MS theses in automated reasoning  Computing Methodologies  ARTIFICIAL INTELLIGENCE 
Domain Adaptation  Computing Methodologies  IMAGE PROCESSING AND COMPUTER VISION 
Domain Adaptation  Computing methodologies  Machine learning 
Dati geografici  Information Systems  INFORMATION SYSTEMS APPLICATIONS 
Analisi e percezione dei segnali biometrici per l'interazione con robot  Robotics  Robotics 
Integrazione del simulatore del robot Nao con Oculus Rift  Robotics  Robotics 
BS or MS theses in automated reasoning  Theory of computation  Logic 
BS or MS theses in automated reasoning  Theory of computation  Semantics and reasoning 
Proposte di tesi/collaborazione/stage in Intelligenza Artificiale Applicata  Various topics 
Proposte di Tesi/Stage/Progetto nell'ambito dell'analisi dei dati  Various topics 
Attendance modes and venues
As stated in the Teaching Regulations, attendance at the course of study is not mandatory.
Parttime enrolment is permitted. Find out more on the Parttime enrolment possibilities page.
The course's teaching activities take place in the Science and Engineering area, which consists of the buildings of Ca‘ Vignal 1, Ca’ Vignal 2, Ca' Vignal 3 and Piramide, located in the Borgo Roma campus.
Lectures are held in the classrooms of Ca‘ Vignal 1, Ca’ Vignal 2 and Ca' Vignal 3, while practical exercises take place in the teaching laboratories dedicated to the various activities.