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Numerical methods of Linear Algebra for Sparse Matrices
В начало
Курсы
Осенний семестр
Магистратура
Num Methods 2025
Module 1. Background in matrix theory and sparse l...
Practical assignment 2. Matrix fundamentals: types...
Practical assignment 2. Matrix fundamentals: types and structures
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Practical assignment 2.pdf
21 октября 2025, 14:54
◄ Practical assignment 1. Getting started with Matlab
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Course overview 2025
Course textbook
Working with Matlab in SFedU and getting started
Lecture notes for Module 1
Practical assignment 1. Getting started with Matlab
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
Practical assignment 3. Vector and matrix norms. Existence of solution, solving linear system in Matlab ►