Polynomial Characteristic and Eigenvalues

Related lectures (29)

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

Explores characteristic polynomials, eigenvalues, and eigenvectors of matrices A, B, C, D, and E.

Explains the characteristic polynomial of a matrix and its importance in linear algebra.

Explores eigenvalues, diagonalization, and matrix similarity, showcasing their importance and applications.

Explores the diagonalization of matrices and the conditions for exact diagonalization, with examples demonstrating the process.

Covers eigenvalues, eigenvectors, and matrix similarity for dynamic systems.

Explores the analysis of free states and modes in multivariable control systems, emphasizing stability properties and practical examples.

Covers eigenvalues, eigenvectors, and the Fibonacci sequence, exploring their mathematical properties and practical applications.

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