Construction of an Iterative Method

Related lectures (25)

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Covers direct methods for solving linear systems in numerical analysis.

Covers the Jacobi method, Givens rotation, QR decomposition, and diagonalization techniques in computational physics.

Explores matrix decompositions for solving linear systems and simulating dynamics.

Covers the concept of Singular Value Decomposition (SVD) for compressing information in matrices and images.

Explores the unique decomposition of matrices into diagonalizable and nilpotent parts, showcasing their properties and applications.

Covers linear systems, diagonal and triangular matrices, and LU factorization.

Covers the basics of linear algebra, including matrix operations and singular value decomposition.

Covers iterative methods for solving linear systems and discusses convergence criteria and spectral radius.

Covers the LU decomposition method applied to linear systems, presenting the system in two steps.

Explores Singular Value Decomposition, low-rank approximation, fundamental subspaces, and matrix norms.