Precision Problems: Hilbert Matrix

Related lectures (29)

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Covers the concept of the matrix of cofactors and a formula to calculate the inverse of a matrix.

Covers matrix eigenvalues, eigenvectors, and their linear independence.

Covers LU factorization, linear independence, and matrix equations.

Explores the equivalence between different properties of linear transformations represented by matrices and various matrix operations.

Covers the composition and product of matrices, including matrix multiplication.

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

Covers the analysis of linear systems, focusing on methods such as Jacobi and Richardson for solving linear equations.

Covers matrix transposition, rank, and basis change in linear algebra, exploring invertibility criteria and basis relationships.

Explains linear independence, basis, and matrix rank with examples and exercises.

Covers the reduction of a linear application and finding corresponding reduced forms and bases.