Generalized minimal residual method

Related lectures (11)

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Explores Newton's method for dynamical systems, GMRES, FGMRES, optimization, multishooting, and trust-region methods.

Covers the conjugate gradient method, stopping criteria, and convergence properties in iterative optimization.

Explores the heat equation solutions using Fourier series and energy conservation.

Covers continuum mechanics, linear elasticity, force balance, divergence, finite element discretization, energy minimization, and Newton's method.

Covers the computation of elastic energy in solid mechanics and equilibrium steps using conjugate gradients.

Delves into the complexity of matrix computations, focusing on eigenvalues and eigenvectors, algorithms, errors, and numerical stability.

Explores iterative methods for solving linear systems and multigrid concepts to improve accuracy and convergence.

Explains the Jacobi and Gauss-Seidel methods for solving linear systems iteratively.

Covers the concept of the spectrum in quantum physics, including invertibility, eigenvalues, and observables.

Explores subspaces, approximation problems, and least-squares approximation methods.