Lectures related to Linear Systems Resolution

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

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

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

Explores the Cholesky factorization method for symmetric positive definite matrices.

Covers the construction of an iterative method for linear systems, emphasizing matrix decomposition and convexity.

Covers the construction of an iterative method for linear systems by decomposing a matrix A into P, T, and P_A.

Covers direct methods for solving linear systems in numerical analysis.

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

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

Explains the concept of least squares solutions and their application in finding the closest solution to a system of equations.

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

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

Explores the properties of invertible matrices, including unique solutions and linear independence.

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

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

Explores matrix decompositions for solving linear systems and simulating dynamics.

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

Covers the formulation of linear systems, direct and iterative methods for solving them, and the cost of LU factorization.

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

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.