Lectures related to Iterative Methods for Linear Equations

Explores quadratic forms, symmetric bilinear forms, and their properties.

Explores the classification of quadratic forms based on eigenvalues and orthogonal diagonalization of symmetric matrices.

Explores complex roots, conjugate pairs, and quadratic equations solving strategies.

Explores the numerical analysis of nonlinear equations, focusing on convergence criteria and methods like bisection and fixed-point iteration.

Covers optimization methods without constraints, including gradient and line search in the quadratic case.

Provides an overview of conjugate gradient methods, including preconditioning, nonlinear conjugate gradient, and singular value decomposition.

Explores the Cholesky factorization method for symmetric positive definite matrices.