Перейти к основному содержанию
Вы используете гостевой доступ (
Вход
)
Numerical methods of Linear Algebra for Sparse Matrices
В начало
Курсы
Осенний семестр
Магистратура
Num Methods 2025
Общее
Course overview 2025
Course overview 2025
Нажмите на ссылку
Course overview NumMethods-2025 Master.pdf
, чтобы просмотреть файл.
Перейти на...
Перейти на...
Course textbook
Working with Matlab in SFedU and getting started
Lecture notes for Module 1
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, solving linear system in Matlab
Practical assignment 4. Gram-Schmidt and QR-factorization
Practical assignment 5. Eigenvalues and their multiplicities, matrix factorizations, Hermitian and positive definite matrices
Practical assignment 6. Schur, LU- and Cholessky factorizations of Hermitian positive definite matrices. Solving linear systems using LU- and Cholessky factorizations.
Practical assignment 7. Condition number, computational costs, well- and ill-conditioned problems
Practical assignment 8. Permutations, reordering and fill-ins
Practical assignment 9. Sparse storage and sparse formats
Practical assignment 10. Comparison of direct and iterative methods for different sparse systems
Course textbook ►