A process named for Cholesky decomposes these objects into the product of a lower- triangular matrix with its adjoint. These objects are always orthogonally diagonalizable, and are positive- definite if and only if all their eigenvalues are positive. Different eigenspaces of these objects produce orthogonal eigenvectors, and according to the (*) spectral theorem, these objects always have orthonormal bases of eigenvectors; thus, all these types of matrices' eigenvalues are real. Generalized by Hermitian matrices, for 10 points, name these types of matrices that are equal to their transpose, wi
A process named for Cholesky decomposes these objects into the product of a lower- triangular matrix with its adjoint. These objects are always orthogonally diagonalizable, and are positive- definite if and only if all their eigenvalues are positive. Different eigenspaces of these objects produce orthogonal eigenvectors, and according to the (*) spectral theorem, these objects always have orthonormal bases of eigenvectors; thus, all these types of matrices' eigenvalues are real. Generalized by Hermitian matrices, for 10 points, name these types of matrices that are equal to their transpose, with entries i,j always equal to entries j,i.
A process named for Cholesky decomposes these objects into the product of a lower- triangular matrix with its adjoint.
{symmetric} matrices [accept word forms; prompt on {matrix} before “types of” is read]