Linear Algebra: Canonical Basis

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Explores the diagonalization of matrices and the conditions for exact diagonalization, with examples demonstrating the process.

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

Explores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.

Covers matrices, linear applications, vector spaces, and bijective functions.

Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.

Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.

Explores canonical basis, linear mapping, and eigenvalues in linear algebra.

Explores eigenvalues and eigenvectors in 3D linear algebra, covering characteristic polynomials, stability under transformations, and real roots.

Covers matrix eigenvalues, eigenvectors, and their linear independence.

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.