Jordan matrix

Related lectures (30)

Covers phase portraits, eigenvalue decomposition, Jordan decomposition, and stable nodes in non-linear systems.

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

Covers eigenvalues, eigenvectors, and characteristic polynomials in matrix transformations.

Covers the second criterion of diagonalization and similar matrices in linear applications.

Illustrates examples of non-diagonalizable matrices with a single eigenvalue.

Explores the diagonalizability of matrices, linear transformations, and matrix representations with practical examples.

Covers the definition and properties of determinants for square matrices, including elementary operations and Lagrange's theorem.

Explores geometric and algebraic multiplicities in diagonalization of linear transformations.

Explains how to determine the geometric multiplicity of an eigenvalue in a matrix.

Covers linear systems in continuous time, stability analysis, and mass-spring system examples.

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