Decomposition of Linear Operators

Related lectures (30)

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Explores the uniqueness of minimal polynomials and the division algorithm for polynomials.

Explores minimal annihilating polynomials and cyclic invariant subspaces, showcasing their practical applications through matrix computations.

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

Explores basis transformation, eigenvalues, and linear operators in inner product spaces, emphasizing their significance in Quantum Mechanics.

Explores division polynomials, theorems, spectral values, and minimal polynomials in endomorphisms and vector spaces.

Explores eigenvalues and minimal polynomial, emphasizing their importance in linear algebra.

Covers eigenvalues, eigenvectors, and their applications in linear algebra.

Covers the concept of eigenvalues and eigenvectors in linear algebra, focusing on the properties of endomorphisms.

Explains the diagonalization of matrices, criteria, and significance of distinct eigenvalues.

Covers the factorization of polynomials with complex coefficients and diagonalizability of matrices.