Linear Systems: Chapters 4, 5, 6

Related lectures (27)

Page 1 of 3

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

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

Covers the resolution of linear systems and its link to optimization problems.

Explores optimal control and KKT conditions for non-linear optimization with constraints.

Covers direct methods for solving linear systems in numerical analysis.

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

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

Explores the Cholesky factorization method for symmetric positive definite matrices.

Explores direct methods for solving linear systems of equations, including Gauss elimination and LU decomposition.

Covers semi-definite programming and optimization over positive semidefinite cones.