# The UD RLS algorithm for training feedforward neural networks

International Journal of Applied Mathematics and Computer Science (2005)

- Volume: 15, Issue: 1, page 115-123
- ISSN: 1641-876X

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topBilski, Jarosław. "The UD RLS algorithm for training feedforward neural networks." International Journal of Applied Mathematics and Computer Science 15.1 (2005): 115-123. <http://eudml.org/doc/207720>.

@article{Bilski2005,

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.},

author = {Bilski, Jarosław},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {learning algorithms; neural networks; UD factorization; recursive least squares method},

language = {eng},

number = {1},

pages = {115-123},

title = {The UD RLS algorithm for training feedforward neural networks},

url = {http://eudml.org/doc/207720},

volume = {15},

year = {2005},

}

TY - JOUR

AU - Bilski, Jarosław

TI - The UD RLS algorithm for training feedforward neural networks

JO - International Journal of Applied Mathematics and Computer Science

PY - 2005

VL - 15

IS - 1

SP - 115

EP - 123

AB - 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.

LA - eng

KW - learning algorithms; neural networks; UD factorization; recursive least squares method

UR - http://eudml.org/doc/207720

ER -

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