Lectures related to Untitled | EPFL Graph Search

Explores bases, dimension, linear independence, and vector space properties.

Covers matrix equations as linear combinations, vector spaces, and geometric interpretations.

Explores vector spaces, subspaces, bases, and linear combinations in R² and R³, including free and linked families.

Covers the Gram-Schmidt algorithm for orthonormal bases in vector spaces.

Covers the spectral decomposition of matrices and change of basis applications.

Covers the decomposition of a matrix into its eigenvalues and eigenvectors, the orthogonality of eigenvectors, and the normalization of vectors.

Explores the Hamilton-Jacobi equation in analytical mechanics, focusing on eigenvalues, constants of motion, and system predictability.

Introduces the concept of basis and canonical basis in linear algebra, essential for vector space representation.

Covers the basics of finite fields, including arithmetic operations and properties.