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Paper details
Number 1 - March 2005
Volume 15 - 2005
The UD RLS algorithm for training feedforward neural networks
Jarosław Bilski
Abstract
A new algorithm for training feedforward multilayer neural networks is proposed. It is based on recursive least squares procedures and U-D factorization, which is a well-known technique in filter theory. It will be shown that due to the U-D factorization method, our algorithm requires fewer computations than the classical RLS applied to feedforward multilayer neural network training.
Keywords
neural networks, learning algorithms, recursive least squares method, UD factorization