Перейти к основному содержанию
Вы используете гостевой доступ (
Вход
)
Exam
В начало
Курсы
Весенний семестр
Магистратура
Num Methods 2026
Exam
Оглавление секции
◄
Classroom examples
Module 1. Background in matrix theory and sparse linear systems
►
Выбрать элемент Exam procedure
Exam procedure
Файл
Выбрать элемент Exam program
Exam program
Файл
◄
Classroom examples
Перейти на...
Главная страница курса
General info and teams for the course
Lectures
Classroom examples
Exam
Module 1. Background in matrix theory and sparse linear systems
Practical assignment 1. Getting started with Matlab
Practical assignment 2. Matrix fundamentals: types and structures
Practical assignment 3. Vector and matrix norms. Existence of solution
Practical assignment 4. Gram-Schmidt and QR-factorization
Practical assignment 5. Eigenvalues multiplicities, matrix factorizations, LU- and Cholesky factorizations
Practical assignment 6. Normal, hermitian and positive definite matrices
Practical assignment 7. Condition number, permutation and reordering, sparse formats
Module 2. Direct and iterative methods. Krylov subspace methods for sparse linear systems and preconditioning techniques
Practical assignment 8. Comparison of direct and iterative methods for different sparse systems
Practical assignment 9 for CM group. Classical iterative methods
Practical assignment 10 for CM group. Krylov subspace methods. FOM and GMRES
Module 1. Background in matrix theory and sparse linear systems
►