Jordan Form: Decomposition and Properties

Related lectures (28)

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Explores spectral and singular value decompositions of matrices.

Covers the construction of an iterative method for linear systems, emphasizing matrix decomposition and convexity.

Covers Jordan form, diagonalization, and nilpotent matrices, discussing properties and decomposition.

Covers the decomposition of matrices into triangular blocks and spectral decomposition.

Explores spectral decomposition of symmetric matrices and Singular Value Decomposition (SVD) for matrix decomposition.

Explores harmonic forms on Riemann surfaces and the uniqueness of solutions to harmonic equations.

Provides an overview of symmetric matrices, quadratic forms, and their applications in linear algebra and analysis.

Explores Singular Value Decomposition, low-rank approximation, fundamental subspaces, and matrix norms.

Covers the construction of an iterative method for linear systems by decomposing a matrix A into P, T, and P_A.

Covers the process of diagonalizing matrices, focusing on symmetric matrices and the spectral theorem.