Elementary Matrices and Matrix Factorization

Related lectures (26)

Page 2 of 3

Covers LU factorization, determinants, subspaces, and matrix products.

Explores elementary matrices in linear algebra and their role in matrix transformations.

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

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

Covers the composition and product of matrices, including matrix multiplication.

Covers matrix operations, focusing on the product and inverse of matrices.

Covers LU factorization, linear independence, and matrix equations.

Provides an overview of symmetric matrices, quadratic forms, and their applications in linear algebra and analysis.

Covers matrix invertibility, determining if a matrix is invertible, calculating its inverse, and elementary matrices.

Covers the LU decomposition algorithm, transforming a matrix into L and U.