Eigenvalues and Eigenvectors

Related lectures (26)

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Explores the effect of rounding errors in solving linear systems using the LU factorization method.

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

Covers the analysis of linear systems, focusing on methods such as Jacobi and Richardson for solving linear equations.

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

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

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

Covers matrix eigenvalues, eigenvectors, and their linear independence.

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

Covers the Singular Value Decomposition (SVD) in detail, including properties of matrices and system linearity.

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