Previous |  Up |  Next

Article

References:
[1] G. Eckart, G. Young: The approximation of one matrix by another of lower rank. Psychometrika / (1936), 211-218.
[2] G. H. Golub, C. Van Loan: An analysis of the total least squares problem. SIAM J. Numer. Anal. 17 (1980), 883-843. MR 0595451 | Zbl 0468.65011
[3] G. H. Golub A. Hoffmann, G. W. Stewart: A generalization of the Eckart-Young-Mirsky matrix approximation theorem. Linear Algebra Appl. 88/89 (1987), 317-327. MR 0882452
[4] U. Helmke, J. B. Moore: Optimization and Dynamical Systems. Springer-Verlag, Berlin 1993. MR 1299725
[5] U. Helmke, M. A. Shayman: Critical points of matrix least squares distance functions. Linear Algebra Appl., to appear. MR 1317470 | Zbl 0816.15026
[6] N. J. Higham: Computing a nearest symmetric positive semidefinite matrix. Linear Algebra Appl. 103 (1988), 103-118. MR 0943997 | Zbl 0649.65026
[7] B. De Moor, J. David: Total linear least squares and the algebraic Riccati equation. Systems Control Lett. 5 (1992), 329-337. MR 1180311 | Zbl 0763.93085
[8] J. B. Moore R. E. Mahony, U. Helmke: Recursive gradient algorithms for eigenvalue and singular value decomposition. SIAM J. Matrix Anal. Appl., to appear. MR 1282700
Partner of
EuDML logo