[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