The UD RLS algorithm for training feedforward neural networks - Bilski, Jarosław (Zielona Góra: Uniwersytet Zielonogórski)
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