Lectures related to Singular Value Decomposition, Pseudoinverse

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

Covers the Singular Value Decomposition (SVD) of a matrix and its applications.

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

Covers the theory and applications of Singular Value Decomposition in computational physics, including solving linear systems and polynomial fits.

Explores applications of linear algebra in image and signal processing, and introduces algorithms like Gaussian elimination and LU decomposition.

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

Covers the Singular Value Decomposition theorem and its applications in practice.