Lecture
Linear Systems Resolution
Related lectures (42)
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Explores LU decomposition for solving linear systems, focusing on determinants and cofactors.
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Introduces LU decomposition for efficient linear equation solving using matrix factorization.
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Covers the Choleski factorisation method for solving linear systems efficiently.
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Covers the decomposition of symmetric matrices into eigenvalues and eigenvectors.
Matrix Decomposition: Triangular and Spectral
Covers the decomposition of matrices into triangular blocks and spectral decomposition.
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Explores linear systems, direct methods, Gauss elimination, LU decomposition, and computational complexity.
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Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.
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Explores direct methods for solving linear equations and the impact of errors on solutions and matrix properties.
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Covers the basics of linear algebra, including matrix operations and singular value decomposition.
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Explores symmetric matrices, their diagonalization, and properties like eigenvalues and eigenvectors.