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Магистратура
Num Methods 2026
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Lecture topics with dates
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Выбрать элемент Lecture 1. Fundamentals of Linear Algebra. Introduction of elementary notation
Lecture 1. Fundamentals of Linear Algebra. Introduction of elementary notation
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Выбрать элемент Lecture 2. Types and structures of square matrices. Vector and matrix norms
Lecture 2. Types and structures of square matrices. Vector and matrix norms
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Выбрать элемент Lecture 3. Existence of solution. Orthogonality, Gram-Schmidt, QR
Lecture 3. Existence of solution. Orthogonality, Gram-Schmidt, QR
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Выбрать элемент Lecture 4. Matrix factorizations (QR, LU, Cholesky)
Lecture 4. Matrix factorizations (QR, LU, Cholesky)
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Выбрать элемент Lecture 5. Eigenvalues multiplicities. Canonical forms. Diagonal, jordan, schur, svd
Lecture 5. Eigenvalues multiplicities. Canonical forms. Diagonal, jordan, schur, svd
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Выбрать элемент Lecture 6. Positive definite, Normal and Hermitian matrices. Perturbation analysis
Lecture 6. Positive definite, Normal and Hermitian matrices. Perturbation analysis
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Выбрать элемент Lecture 7. Graph representations of sparse matrices. Permutations and reordering
Lecture 7. Graph representations of sparse matrices. Permutations and reordering
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Выбрать элемент Lecture 8. Storage schemes for sparse matrices. Discretization of PDE (overview)
Lecture 8. Storage schemes for sparse matrices. Discretization of PDE (overview)
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Выбрать элемент Lecture 9. Discretization of PDEs. Finite difference method
Lecture 9. Discretization of PDEs. Finite difference method
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Выбрать элемент Lecture 10. Overview of FEM. Direct and iterative methods. General formulation of iterative method
Lecture 10. Overview of FEM. Direct and iterative methods. General formulation of iterative method
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Выбрать элемент Lecture 11. Classical iterative methods
Lecture 11. Classical iterative methods
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Выбрать элемент Lecture 12. Projection methods. 1D projection methods
Lecture 12. Projection methods. 1D projection methods
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Выбрать элемент Lecture 13. Krylov subspace methods. FOM
Lecture 13. Krylov subspace methods. FOM
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Выбрать элемент Lecture 14. Krylov subspace methods. GMRES
Lecture 14. Krylov subspace methods. GMRES
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Выбрать элемент Lecture 15. FOM and GMRES. Lanczos process. Preconditioning techniques
Lecture 15. FOM and GMRES. Lanczos process. Preconditioning techniques
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Выбрать элемент For Lecture 15. Derivation of CG
For Lecture 15. Derivation of CG
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General info and teams for the course
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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
Classroom examples
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