LEARNING OUTCOMES

The course aims to offer the mathematical and methodological notions that are the basis of the techniques of scientific calculus. An integral part of the course is to consider the laboratory exercises where the student experiences and verifies the theory taught in lesson.

SYLLABUS/CONTENT

Error theory. Solution of linear systems: conditioning, Gauss' method and pivoting, matrix factorization: LU and Cholsky; applications. Eigenvalues: power method and extensions, similarity transformations, Householder transformation; QR factorization; reduction to Hessenberg and tridiagonal forms, QR method. Approximation of functions: discrete least-squares: solution by means of normal equations. Singular Value Decomposition and application to the least-squaresproblem. Numerical solution of differential equations by means one step and multistep methods.

Laboratory: 5 exercises about topics addressed during the semester (the use of Matlab is required)