Numerical Linear Algebra
Keywords |
Classification |
Keyword |
OFICIAL |
Mathematics |
Instance: 2022/2023 - 2S
Cycles of Study/Courses
Teaching language
Portuguese
Objectives
It is intended that the student acquires fundamental techniques and methods of Numerical Linear Algebra in its theoretical and practical aspects, namely in the development of algorithms, computational implementation and experimentation in the MATLAB or GNU Octave language. The student should use these methods for solving problems in applications.
Learning outcomes and competences
The student should be able to interpret the Linear Numerical Algebra methods taught, implement them in a computer, test them and use them in problem solving.
Working method
Presencial
Pre-requirements (prior knowledge) and co-requirements (common knowledge)
Basic knowledge of Linear Algebra, and computational programming in any language.
Program
I – Numerical resolution of systems of linear equations and numerical computation of inverses of matrices. Vector and matrix norms. Gram-Schmidt orthonormalization. Conditioning and stability. Condition numbers. Matrix types. Elementary matrix and transformations. Triangular systems. Gauss elimination and LU factorization with pivoting. Computation of inverse matrix. Positive definite matrix. Cholesky method. QR decomposition. Iterative methods of Jacobi and Gauss-Seidel. Applications.
II – Numerical computation of eigenvalues and eigenvectors. Gersgorin location. Direct and inverse power methods. Orthogonal matrix. Singular value decomposition (SVD). Pseudoinverse. Least square solution of linear systems. QR-algorithms. Applications.
Mandatory literature
William Ford;
Numerical linear algebra with applications. ISBN: 978-0-12-394435-1
Alfio Quarteroni, Fausto Saleri; Calculo Científico com Matlab e Octave, Springer, 2007. ISBN: 978-88-740-0717-8
Teaching methods and learning activities
Exposition of the contents of the syllabus complemented by the presentation of illustrative examples.
Computational implementation in the MATLAB or GNU Octave language of concepts and methods acquired. Use of the methods taught in problems solving in applications.
Software
GNU Octave
Matlab
Evaluation Type
Distributed evaluation without final exam
Assessment Components
designation |
Weight (%) |
Prova oral |
25,00 |
Teste |
50,00 |
Trabalho escrito |
25,00 |
Total: |
100,00 |
Amount of time allocated to each course unit
designation |
Time (hours) |
Apresentação/discussão de um trabalho científico |
1,00 |
Elaboração de projeto |
25,00 |
Estudo autónomo |
53,00 |
Frequência das aulas |
56,00 |
Trabalho escrito |
2,00 |
Trabalho laboratorial |
25,00 |
Total: |
162,00 |
Eligibility for exams
Realization of a project with report and oral presentation.
Calculation formula of final grade
Test with computacional part: 50%
Report: 25%
Oral presentation: 25%
Classification improvement
Only in the part corresponding to the test.