Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1141358 | Mathematics and Computers in Simulation | 2006 | 13 Pages |
Abstract
The training of some types of neural networks leads to separable non-linear least squares problems. These problems may be ill-conditioned and require special techniques. A robust algorithm based on the Variable Projections method of Golub and Pereyra is designed for a class of feed-forward neural networks and tested on benchmark examples and real data.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
V. Pereyra, G. Scherer, F. Wong,