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  1. Courses

SCC0302 - NUMERICAL ANALYSIS

courses
ID:
SCC0302
Duration (hours):
68
CFU:
8
SSD:
ANALISI NUMERICA
Year:
2025
  • Overview
  • Syllabus
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Overview

Date/time interval

Secondo Semestre (23/02/2026 - 12/06/2026)

Syllabus

Course Objectives

The present lectures contribute to the broader educational objectives of the CdS in Mathematics, as it aims to provide students with the knowledge of the critical analysis of algorithms and of their complexity and numerical stability. The course also aims to educate the student in the constructive demonstration and the algorithmic view of mathematics, starting from Linear Algebra and Matrix Theory. EXPECTED LEARNING OUTCOMES At the end of the course, the student is expected to be able to: 1. carry out an a priori analysis of linear systems to verify the invertibility or strong nonsingularity or definiteness in sign of the coefficient matrix 2. on the basis of point 1., choose the most efficient numerical resolution technique, i.e. the least expensive in terms of the number of operations and with the best possible stability features 3. carry out rank analysis of large matrices 4. choose the most appropriate technique for calculating eigenvalues and eigenvectors, also in relation to very large problems such as the Google PageRanking computation

Course Prerequisites

Programming, Lab. Computational Mathematics, Linear Algebra, Analysis.

Teaching Methods

Lectures occupy three-quarters of the teaching hours; a quarter is devoted to exercises. Lectures are always on the blackboard: an education in flexibility will be favoured (there is never just one way to prove a mathematical assertion) The exercises often deal with 'complex' problems that can be considered as complements to the theory and an introduction to research The more complex topics are dealt with by the teacher; the more standard exercises are entrusted to a qualified tutor

Assessment Methods

The written exam is a barrier for access to the oral exam, i.e. without a minimum level a student cannot access the oral exam: - the written test lasts three hours, it contains exercises that are never standard, the student can bring any kind of material they consider necessary (except communication tools, as phones, PC etc) - individual points are hidden among the exercises where imagination is required: such points are aimed at finding students with talent for research - the exercises can be solved in various ways: those who find a faster and more elegant way (minimising the amount of maths) will be assessed more positively - the oral test aims to check the level of mathematical rigour acquired by the student - the final grade starts from that of the written paper by adding at most 8 points depending on the outcome of the oral part. If the oral part is particularly lacking, the student will be invited to appear later for the oral part only

Contents

Matrix theory. Unitary matrix, Hermitian, definite positive, normals. Normal forms: Schur and Jordan Spectral characterisation of unitary, Hermitian, positive definite, normal matrices by Schur Eigenvalues: localisation (Gerschgorin Theorems I, II, III), vector norms, matrix norms, induced norms (relations between spectral radius and induced norms) Topological equivalence theorem of norms on finite-dimensional vector spaces Elementary matrices (spectral, inverse characterisation): Gauss, Householder Numerical solving of linear systems: linear systems in special form (unitary matrix, triangular etc.) Problem conditioning and stability Numerical resolution of linear systems: Gauss elimination, pivoting, QR factorisation Choleski algorithm for positive definite matrices Shermann-Morrison-Woodbury formula (efficient update techniques) Numerical stability of direct resolution algorithms Iterative methods: general theory, Jacobi and Gauss-Seidel methods (convergence analysis) Calculation of eigenvalues using the method of powers and variants. Example of the Google Pageranking case Evaluation of a polynomial at a point. Interpolation. Vandermonde matrix.

Course Language

Italian

More information

Ricevimento su appuntamento tramite email: stefano.serrac@uninsubria.it

Degrees

Degrees

MATHEMATICS 
Bachelor’s Degree
3 years
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People

People

SERRA CAPIZZANO STEFANO
AREA MIN. 01 - Scienze matematiche e informatiche
Gruppo 01/MATH-05 - ANALISI NUMERICA
Settore MATH-05/A - Analisi numerica
Docenti di ruolo di Ia fascia
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