60/64/179 - NUMERICAL ANALYSIS
Academic Year 2018/2019
Free text for the University
DANIELA LERA (Tit.)
- Teaching style
- Lingua Insegnamento
|[60/64] MATHEMATICS||[64/00 - Ord. 2017] PERCORSO COMUNE||12||96|
KNOWLEDGE AND UNDERSTANDING.
The knowledge of the goal and guidelines of Numerical Analysis: well-posed and ill-conditioned problems, algorithms, errors, floating point systems, computational complexity, stability. Knowledge of the basic techniques for solving linear systems, approximation theory, nonlinear equations and differential equations.
APPLYING KNOWLEDGE AND UNDERSTANDING
The student, from the initial formulation of a numerical problem, must be able to find, if they exist, the numerical solutions and to evaluate the accuracy and the computational cost. In particular, the exercises, that are an important part of the course, are intended to develop the ability to identify the most suitable approach to the solution of the problems.
The course encourages students to work independently even in order to use alternative sources of information to educational material provided by the teacher. These sources can be other educational material available on the net, software, tutorials, interactive web of numerical analysis problems.
The course aims to achieve by the student not only the understanding of a subject, but also the exhibition capacity according to the formal rigor required by the Numerical Analysis. For this reason is provided a oral examination on some "key" topics of the course.
The lectures were held so that they pass to elementary situations (definitions, theorems and methods) of immediate assimilation to complex situations. The exercises, which are performed alternately to lectures, have the task, in addition to developing the application spirit, to facilitate the learning of concepts and mathematical results.
A) Basic concepts of mathematical analysis: Sets. Functions of one or more variables. Continuity and derivability. Integration.
B) Basic knowledge of linear algebra. Vectors and Matrices. Determinant and rank. Linear Spaces. Finite and infinite spaces.
Fundamental Notions. Linear spaces. Norms of vectors and matrices.
Floating point arithmetic and rounding errors.
Computer representation of numbers
Definitions and sources of error.
Systems of linear equations. Direct methods. Iterative methods.
Function approximation. Interpolation. Best Approximation.
Numerical Integration. Iterpolatory quadrature. Newton-Cotes formulas. Gaussian quadrature.
Systems of nonlinear equations. Bisection method. Newton's method. Secant methods. Theory for one-point iteration methods.
Numerical solutions of ordinary differential equations.
Lectures. Computer and laboratory exercises.
48 hours of lesson and 48 hours of laboratory exercise.
The teaching material can be found on the teaching website:
The exercises consist of the realization of the Matlab programs related to the methods studied in the lessons; In particular, the student, initially under the guidance of the teacher, must implement the algorithms indicated and resolve independently exercises.
Verification of learning
The student will be evaluated on: acquisition of methods, knowledge of disciplinary language, ability to relate concepts and knowledge, exhibition capacity.
The exne è di almeno 18/30. Il tempo massimo delle prove scam consists of a written test followed by an oral. Passing the first is necessary to access the second one.
The written test consists of 20 questions, theoretical or exercises, covering all the topics discussed during the course. The written test is considered to be overcome if the vote is at least 18/30. The maximum test time is two hours.
The oral test consists of an interview during which the student must be able to expose the theoretical arguments and carry out the exercises. In particular it must be able to expose the algorithms studied and use Matlab language programs in the laboratory. The date of the oral examination is agreed with the teacher personally, by telephone or by email.
The final vote is determined by the vote of both tests:
18-23 the student has sufficient knowledge of the basic arguments of the course and is able to use the Matlab programs carried out during the exercises.
24-27 the student has a good knowledge of all the arguments of the course and their Matlab-codes, as well as a good exhibition capacity.
28-30th the student has a perfect knowledge of the arguments of the course and of the Matlab programs, as well as a very good exhibition capacity.
V.Comincioli, Analisi Numerica, metodi modelli applicazioni, McGraw-Hill Libri Italia, srl, Milano 1998.
A.Quarteroni, R. Sacco, F.Saleri: Matematica Numerica, Sprinter-Verlag 1998.
G.Rodriguez: Algoritmi Numerici, Pitagora Editrice, 2008.
J.Stoer, R. Burlisch, Introduzione all''Analisi Numerica, Ed. Zanichelli.
E.Isaacson, H.B.Keller, Analysis of Numerical Methods, John Wiley, New York.
F.Fontanella, A. Pasquali, Calcolo Numerico, Metodi ed Algoritmi, Ed. Pitagora, Bologna.
W.J Palm III, Matlab 6, Mc Graw-Hill.
W.H. Press et alii., Numerical Recipes, The art of Scientific Computing, Cambridge Press.
The notes of the lectures, the practical exercises and the software are made available to the students during the class.
Student reception hours
Tuesday - Thursday 11-13. Afternoon by appointment (you can send me an email)
Our University provides support for students with learning disabilities (DSA). Those interested could find more information at this link: