Linear Systems: Direct Methods

Related lectures (31)

Page 3 of 4

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

Covers the Gaussian elimination method for solving linear equations using row operations on matrices.

Explores linear systems, Cholesky factorization, LU factorization, and matrix precision.

Explains row-echelon and reduced row-echelon matrices and their role in simplifying system resolution.

Explores operations with triangular matrices and their role in solving linear systems.

Explores LU factorization, rounding-off errors, sparse matrices, and matrix operations using MATLAB.

Explores the Cholesky factorization method for symmetric positive definite matrices.

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

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

Covers the basics of LU decomposition, focusing on identifying coefficients of matrices A and LU.