Matrix Functions: Theory and Computation

Related lectures (27)

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

Explores symmetric matrices, their diagonalization, and properties like eigenvalues and eigenvectors.

Introduces Lagrange interpolation for approximating data points with polynomials, discussing challenges and techniques for accurate interpolation.

Explores matrix similarity, diagonalization, characteristic polynomials, eigenvalues, and eigenvectors in linear algebra.

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

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

Explores diagonalization of symmetric matrices and their eigenvalues, emphasizing orthogonal properties.

Explores the method of diagonalization for matrices and the calculation of matrix powers.

Covers the diagonalization of matrices using eigenvectors and eigenvalues.

Explores properties of 3x3 matrices with real coefficients and determinant calculation methods.