Lecture
Diagonalization of Matrices: Eigenvectors and Eigenvalues
Related lectures (126)
Linear Recurrences and Applications
Explores linear recurrences, applications between sets, and the significance of functions and operators in mathematics and physics.
Diagonalisable Matrices and Linear TransformationsMOOC: Algebra (part 1)
Explores diagonalizability for linear transformations and matrices based on eigenvectors and eigenvalues.
Diagonalization: Projectors
Explores diagonalization through projectors and matrices of projection in relation to eigenvalues and eigenvectors.
Forced Oscillator Regime: Generalized Conservative Approach
Explores the forced oscillator regime in vibratory mechanics, emphasizing clean pulsations and a generalized conservative approach.
Linear Algebra: Spectral Decomposition
Covers the spectral decomposition of matrices and change of basis applications.
Eigenvalues, Eigenvectors: Stable Vectorial Lines
Covers stable vectorial lines, eigenvectors, and their properties under linear transformations in R³.
Singular Values, Fundamental TheoremMOOC: Algebra (part 1)
Explores the fundamental theorem on singular values and the formation of orthonormal bases from eigenvectors.
Diagonalization Theory
Covers the theory of diagonalization in linear algebra, including conditions for diagonalizability and examples of diagonalizable matrices.
Diagonalization of Matrices
Explores diagonalization of matrices, conditions, invertibility, rank, nullity, and eigenvectors.
Similar Matrices and Eigenvalues
Explores the relationship between similar matrices and their eigenvalues.