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Numerical Methods of Linear Algebra 2026
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Курсы
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Магистратура
Num Methods 2026
Module 1. Background in matrix theory and sparse l...
Lecture slides for Module 1
Lecture slides for Module 1
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Lecture 1.pdf
Lecture 2. Types and structures of square matrices. Vector and matrix norms.pdf
Lecture 3. Existence of solution. Orthogonality, Gram-Schmidt, QR.pdf
Lecture 4. Matrix factorizations (QR, LU, Cholesky).pdf
Lecture 5. Lecture 5. Eigenvalues multiplicities. Canonical forms. Diagonal, jornan, schur, svd.pdf
Lecture 6. Positive definite, Normal and Hermitian matrices. Perturbation analysis.pdf
Lecture 7. Graph representations of sparse matrices. Permutations and reordering.pdf
Lecture 8. Storage schemes for sparse matrices. Discretization of PDE.pdf
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Lecture recordings for Module 1
Lecture recordings for Module 1 ►