Eigenvalues Reduction: Two Real Eigenvalues

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

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

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

Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.

Explores the unique decomposition of matrices into diagonalizable and nilpotent parts, showcasing their properties and applications.

Covers the process of diagonalizing matrices, focusing on symmetric matrices and the spectral theorem.

Covers systems of n linear first-order ODEs with constant coupling matrix A and explores properties of solutions and the superposition principle.

Explores orthogonally diagonalizable matrices, eigenvectors, bases, and matrix properties.

Covers the properties and calculations of the determinant of a matrix.

Explores the reduction of a linear transformation with a single real eigenvalue.