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 technical-administrative 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.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

For the year 2008/2009 No calendar yet available

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.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

A B C D F G M O P R S V Z

Angeleri Lidia

lidia.angeleri@univr.it 045 802 7911

Baldo Sisto

sisto.baldo@univr.it 045 802 7935

Berardi Andrea

andrea.berardi@univr.it 045 8425452

Bos Leonard Peter

leonardpeter.bos@univr.it +39 045 802 7987

Caliari Marco

marco.caliari@univr.it +39 045 802 7904

Di Palma Federico

federico.dipalma@univr.it +39 045 8027074

Ferro Ruggero

ruggero.ferro@univr.it 045 802 7909

Fraccarollo Luigi

luigi.fraccarollo@unitn.it

Giarola Marco

marco.giarola@univr.it +39 045 802 7975

Magazzini Laura

laura.magazzini@univr.it 045 8028525

Marigonda Antonio

antonio.marigonda@univr.it +39 045 802 7809

Mariotto Gino

gino.mariotto@univr.it +39 045 8027031

Mariutti Gianpaolo

gianpaolo.mariutti@univr.it 045 802 8241

Mastrogiacomo Elisa

Menon Martina

martina.menon@univr.it 045 802 8420

Monti Francesca

francesca.monti@univr.it 045 802 7910

Morato Laura Maria

laura.morato@univr.it 045 802 7904

Orlandi Giandomenico

giandomenico.orlandi at univr.it 045 802 7986

Perali Federico

federico.perali@univr.it 045 802 8486

Pica Angelo

angelo.pica@univr.it

Rossi Francesco

francesco.rossi@univr.it 045 8028067

Sansonetto Nicola

nicola.sansonetto@univr.it 049-8027932

Solitro Ugo

ugo.solitro@univr.it +39 045 802 7977

Spera Mauro

mauro.spera@univr.it +39 045 802 7816
Marco Squassina,  January 5, 2014

Squassina Marco

marco.squassina@univr.it +39 045 802 7913

Venturin Manolo

Zampieri Gaetano

gaetano.zampieri@univr.it +39 045 8027979

Zuccher Simone

simone.zuccher@univr.it

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 enrolment year.

Training offer to be defined

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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S02755

Credits

12

Language

Italian

Scientific Disciplinary Sector (SSD)

MAT/08 - NUMERICAL ANALYSIS

The teaching is organized as follows:

Teoria

Credits

9

Period

1st Semester, 2nd Semester

Academic staff

Leonard Peter Bos

Laboratorio

Credits

3

Period

1st Semester, 2nd Semester

Academic staff

Manolo Venturin

Learning outcomes

Module: Theory
-------
In this course we will study the most important methods for the numerical solution of the classical problems of Mathematical Analysis. Besides the required theoretical background material needed for understanding the subject, particular emphasis will be placed on algorithms, including their implementation, their complexity and efficiency, as well as the purely numerical problems of convergence and stability. The objective is thus not just to provide the student with a knowledge of the methods, but also to cultivate a "numerical intution" which is important for solving real world problems.

Module: Laboratory
-------
The implementation in Matlab and/or GNU Octave of the basic algorithms of Numerical Analysis.

Program

Module: Theory
-------
* Error Analysis
Representation of numbers. Absolute error and relative error. Machine numbers and associated errors. Algoriths for evaluating an expression. Conditioning of problems and the stability of methods.
* Non-linear Equations
The bisection method. Fixed point methods: generality, convergence and stopping criteria. The secant method, Newton's method and Aitken acceleration. Algebraic polynomials: Horner's rule.
* Linear Systems
Direct methods: LU factorization and pivoting, forward and back substitution, fast algorithms for tridiagonal systems.
Iterative methods: Jacobi iteration, Gauss-Seidel and SOR. Iterative improvement. Richardson's method and the gradient method. Sparse and banded systems. Solution of over and under determined systems. Solution of poorly conditioned systems.
* Eigenvalues and Eigenvectors
Localization of eigenvalues: Gerschgorin circles. The power method and the inverse power method. The QR method and its variants. Eigenvalues of tridiagonal matrices: Schur's method.
* Interpolation and Approximation of Functions and Data.
Polynomial interpolation: the Newton and Lagrange form. Approximation error estimates. Trigonometric interpolation and the the Fast Fourier Transform (FFT). Piecewise polynomial interpolation and splines. Least squares and the SVD.
* Numerical Differentiation and Integration.
Simple formulas for approximating derivatives and their relative error.
Numerical integration or quadrature: interpolation based formulas, both simple and composite. Error in quadrature. Adaptive methods. Gaussian quadrature.
* Numerical Solution of Ordinary Differential equations (ODE).

Examination Methods

What the student has learned will be tested by means of an Oral Exam. In the first part you will be asked to discuss a number of the exercises given during the Laboratory. Then you will be asked some questions regarding the theory discussed during the lectures. The student is to bring with them their exercise notes and problem solutions to the exam.

Hence attending the Laboratory and solving the assigned problems are necessary in order to be able to pass the exam.

Type D and Type F activities

Training offer to be defined

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.

Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.


Graduation

Attachments

List of theses and work experience proposals

theses proposals Research area
Formule di rappresentazione per gradienti generalizzati Mathematics - Analysis
Formule di rappresentazione per gradienti generalizzati Mathematics - Mathematics
Mathematics Bachelor and Master thesis titles Various topics
Stage Research area
Internship proposals for students in mathematics Various topics

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, except for specific practical or lab activities, attendance is not mandatory. Regarding these activities, please see the web page of each module for information on the number of hours that must be attended on-site.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Career management


Area riservata studenti