Construction of an Iterative Method

Related lectures (27)

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Covers the QR factorization method applied to solving a system of linear equations in the least squares sense.

Explores matrix inversion, conditions for invertibility, uniqueness of the inverse, and elementary matrices for inversion.

Explores LU decomposition for solving linear systems and the associativity of operations.

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

Explains the Jacobi and Gauss-Seidel methods for solving linear systems iteratively.

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

Covers the Singular Value Decomposition (SVD) in detail, including properties of matrices and system linearity.

Covers direct methods for solving linear systems in numerical analysis.

Explores LU decomposition of a matrix into lower and upper triangular matrices.

Covers the QR factorization of a matrix A into Q and R.