Iterative Methods for Linear Equations

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Page 2 of 3

Explores symmetric matrices, quadratic forms, diagonalization, and definiteness with examples and calculations.

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

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

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

Explores the effect of rounding errors in solving linear systems using the LU factorization method.

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

Covers iterative methods for solving linear systems and discusses convergence criteria and spectral radius.

Explores the Newton method for non-linear equations, discussing convergence criteria and stopping conditions.

Explores the theory of Hermitian spaces and their applications in quadratic forms and codimension 1 spaces.