Definite matrix

Related lectures (30)

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Explores Sylvester's Inertia Theorem, relating eigenvalues to diagonal entries in symmetric matrices.

Covers the basics of linear algebra, including matrix operations and singular value decomposition.

Covers the Cholesky decomposition of a symmetric positive definite matrix and its applications.

Delves into the proof of the convergence rate theorem for an ergodic Markov chain, emphasizing eigenvalues and detailed balance properties.

Explores the geometric equivalence of Coxeter groups with the same graph and positive definite matrices.

Explores symmetric matrices, quadratic forms, diagonalization, and definiteness with examples and calculations.

Explores direct methods for solving linear equations and the impact of errors on solutions and matrix properties.

Covers linear systems, diagonal and triangular matrices, and LU factorization.

Covers the design of SISO polynomial controllers using concepts such as the Sylvester matrix and model matching.

Introduces Convex Optimization notation, convex functions, vector norms, and matrix properties.