Least squares solutions of the matrix equation AXB + CYD = E with the least norm for symmetric arrowhead matrices.
Hongyi LiZongsheng GaoDi ZhaoPublished in: Appl. Math. Comput. (2014)
Keyphrases
- least squares
- singular value decomposition
- positive definite
- matrix inversion
- symmetric matrices
- coefficient matrix
- symmetric matrix
- low rank approximation
- symmetric positive definite
- pseudo inverse
- eigenvalue decomposition
- singular values
- matrix approximation
- boundary value problem
- data matrix
- positive semidefinite matrices
- positive semidefinite
- block diagonal
- covariance matrix
- low rank
- matrix representation
- linear complementarity problem
- square matrices
- low rank matrices
- perturbation theory
- projection matrices
- trace norm
- frobenius norm
- rows and columns
- robust estimation
- low rank matrix approximation
- matrix completion
- measurement matrix
- eigenvalues and eigenvectors
- sparse linear
- systems of linear equations
- binary matrices
- correlation matrix