Eigenvalues and eigenvectors

Related lectures (29)

Explores eigenvalues and eigenvectors, demonstrating their importance in linear algebra and their application in solving systems of equations.

Covers quantum eigenfunctions and the importance of A and B commuting for the same set of eigenfunctions.

Explains the postulates of Quantum Mechanics, focusing on self-adjoint operators and mathematical notation.

Explores the application of matrices and eigendecompositions in networks.

Covers the method of diagonalization for determining if a non-square matrix A is diagonalizable.

Covers matrix eigenvalues, eigenvectors, and their linear independence.

Covers the criteria for diagonalizing a matrix and provides illustrative examples.

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

Explores eigenvalues, eigenvectors, diagonalization, and spectral theorem in linear algebra.

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