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.
Type D and Type F activities
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Mathematics - Enrollment from 2025/2026years | Modules | TAF | Teacher |
---|---|---|---|
1° 2° | Python programming language | D |
Maurizio Boscaini
(Coordinator)
|
1° 2° | SageMath | F |
Zsuzsanna Liptak
(Coordinator)
|
1° 2° | History of Modern Physics 2 | D |
Francesca Monti
(Coordinator)
|
1° 2° | History and Didactics of Geology | D |
Guido Gonzato
(Coordinator)
|
years | Modules | TAF | Teacher |
---|---|---|---|
1° 2° | Advanced topics in financial engineering | D |
Luca Di Persio
(Coordinator)
|
1° 2° | C Programming Language | D |
Sara Migliorini
(Coordinator)
|
1° 2° | C++ Programming Language | D |
Federico Busato
(Coordinator)
|
1° 2° | LaTeX Language | D |
Enrico Gregorio
(Coordinator)
|
years | Modules | TAF | Teacher |
---|---|---|---|
1° 2° | Axiomatic set theory for mathematical practice | F |
Peter Michael Schuster
(Coordinator)
|
1° 2° | Corso Europrogettazione | D | Not yet assigned |
1° 2° | Corso online ARPM bootcamp | F | Not yet assigned |
1° 2° | ECMI modelling week | F | Not yet assigned |
1° 2° | ESA Summer of code in space (SOCIS) | F | Not yet assigned |
1° 2° | Google summer of code (GSOC) | F | Not yet assigned |
1° 2° | Higher Categories - Seminar course | F |
Lidia Angeleri
(Coordinator)
|
Data Fitting and Reconstruction (2019/2020)
Teaching code
4S008269
Academic staff
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
MAT/08 - NUMERICAL ANALYSIS
Period
I semestre dal Oct 1, 2019 al Jan 31, 2020.
Learning outcomes
The course will discuss the theory and practice of approximation of functions and data, in both the univariate and multivariate setting, with an emphasis on splines of various types and interpolation, including subdivsion and other methods for surface reconstruction. A part of the course will be held in a Laboratory setting where some of the techniques presented during the lectures will be implemented in Matlab. At the end of the course the student is expected to be able to demonstrate an in-depth knowledge of the techniques of univariate and multivariate approximation.
Program
The course will discuss the theory and practice of approximation of functions and data, in both the univariate and multivariate setting, with an emphasis on splines of various types and interpolation. A part of the course will be held in a Laboratory setting where some of the techniques presented during the lectures will be implemented in Matlab. At the end of the course the student is expected to able to demonstrate an in-depth knowledge of the techniques of univariate and multivariate approximation.
Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|
C. de Boor | A Practical Guide to Splines (Edizione 1) | Springer | 1978 | ||
L. Bos | Course Notes | 2017 |
Examination Methods
The purpose of the exam is to see if the student is able to recall and reproduce the theory and practice of interpolation and approximation, both univariate and multivariate. The exam will be oral.