Lectures related to Finite Element Modeling: Common Pitfalls

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

Explores the diagonalization of symmetric matrices through orthogonal decomposition and the spectral theorem.

Covers the diagonalization of linear transformations in R^3, exploring properties and examples.

Explains convergence criteria and optimal choices for Richardson iteration method, including error estimation and matrix conditioning.

Explores properties of 3x3 matrices with real coefficients and determinant calculation methods.

Covers visualizations in orthonormal bases in R2, focusing on rotations and reflections.

Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.