Abstract
We describe how to use the conjugate gradient method with Jacobi preconditioning for solving linear or moderately nonlinear least squares problems. The algorithm is suitable for large but sparse problems, and it works even if the problem is ill-conditioned or singular.
Original language | English (US) |
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Pages (from-to) | 539-543 |
Number of pages | 5 |
Journal | Nuclear Inst. and Methods in Physics Research, A |
Volume | 327 |
Issue number | 2-3 |
DOIs | |
State | Published - Apr 1 1993 |
Externally published | Yes |
ASJC Scopus subject areas
- Nuclear and High Energy Physics
- Instrumentation