AIMS AND CONTENT

LEARNING OUTCOMES

after completing this course, the student will be able to:

apply the acquired knowledge on the treatment of experimental data, the numerical calculation, the variational methods;

know how to choose from time to time the best numerical methods for the treatment of the experimental data and the simulation of models.

TEACHING METHODS

Lecture hours: 42; practise hours: 10 (MATLAB)

SYLLABUS/CONTENT

Normed spaces, orthonormal spaces, operators. Function approximation in a normed space, best uniform approximation. Numerical differentiation and integration. Numerical solution of ordinary differential equations (ODE). Compatibility of linear systems. Least squares solution. Singular value decomposition (SVD) of a matrix with applications. Variational calculus: Euler-Lagrange equations. Variational formulation of physico-mathematical models. Approximate solution of linear and nonlinear ODE - PDE by weighted-residual methods. Applications: traffic models, nonlinear propagation.

RECOMMENDED READING/BIBLIOGRAPHY

-) material provided by the lecturer (PdF notes distributed by the teacher)

-) main reference textbook (in Italian): Mauro Parodi: “Metodi matematici per l’ingegneria” Levrotto&Bella ed., Torino, 2013

TEACHERS AND EXAM BOARD

Exam Board

MAURO PARODI (President)

MATTEO LODI

ALBERTO OLIVERI

MARCO STORACE

LESSONS

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Oral examinations. Proofs concern discussion of and critical thinking about course topics.

ASSESSMENT METHODS

after completing this course, the student will be able to:

know how to choose from time to time the best numerical methods for the treatment of the experimental data and the simulation of models;

apply the acquired knowledge on the treatment of experimental data, the numerical calculation, the variational methods to the formulation of physico-mathematical models.

Exam schedule