Abstract
This paper describes a fall-back procedure for use with the Gauss-Newton method for nonlinear least-squares problems. While the basic Gauss-Newton algorithm is often successful, it is well-known that it can sometimes generate poor search directions and exhibit slow convergence. For dealing with such situations we suggest a new two-dimensional search strategy. Numerical experiments indicate that the proposed technique can be effective.
| Original language | English |
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| Pages (from-to) | 435-447 |
| Journal | Advanced Modeling and Optimization |
| Volume | 11 |
| Issue number | 4 |
| Publication status | Published - 2009 |