Article ID Journal Published Year Pages File Type
1141358 Mathematics and Computers in Simulation 2006 13 Pages PDF
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.

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Physical Sciences and Engineering Engineering Control and Systems Engineering
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