Finite precision computation.
Numerical methods for solving scalar nonlinear equations.
Numerical solution of linear systems.
Data and function approximation.
M.G.Gasparo, R. Morandi:
Elementi di Calcolo Numerico:metodi e algoritmi
McGraw-Hill editore, 2008
G. Naldi, L. Pareschi, G. Russo, "Introduzione al calcolo Scientifico, metodi e applicazioni con Matlab", McGraw-Hill, 2001.
Learning Objectives - Last names A-L
Knowledge of the most used numerical methods for solving linear and nonlinear equations, interpolation and regression problems.
Ability to develop an algorithm for the methods studied.
Prerequisites - Last names A-L
Fundamentals of linear algebra and calculus
Teaching Methods - Last names A-L
Lectures (39 hours) and Matlab laboratory (15 hours)
Further information - Last names A-L
The schedule of the exams is available at the webpage of the School of Engineering
Type of Assessment - Last names A-L
Written exam, the cut score for passing is 18/30.
After passing the written exams, the oral exam can be requested by either the teacher or the student.
Course program - Last names A-L
Algorithms. Floating point arithmetics. Finite precision. Norms of matrices and vectors.
Conditioning of a problem.
Stability of an algorithm. Direct methods for linear systems: Gauss method and pivoting strategies. Jacobi and Gauss-Siedel iterative methods for linear systems.
Iterative methods for finding the roorts of a nonlinear equation:
Bisection, Newton and Secant methods; corresponding algorithms.
MATLAB: Handling matrices, operations between matrices. Function and script files.
If, while and for commands.
2D e 3D plots. Built-in functions for linear systems, nonlinear equations, basic fitting.