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Title: The UD RLS algorithm for training feedforward neural networks

Creator:

Bilski, Jarosław

Date:

2005

Resource Type:

artykuł

Group publication title:

AMCS, Volume 15 (2005)

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.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Contributor:

Korbicz, Józef - red. ; Uciński, Dariusz - red.

Resource Identifier:

oai:zbc.uz.zgora.pl:57500

Pages:

115-123

Source:

AMCS, volume 15, number 1 (2005)

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego

Subject and keywords:

neural networks learning algorithms recursive least squares method UD factorization

Object collections:

Last modified:

Aug 17, 2020

In our library since:

Aug 17, 2020

Number of object content hits:

9

All available object's versions:

https://www.zbc.uz.zgora.pl/publication/64048

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The UD RLS algorithm for training feedforward neural networks Aug 17, 2020

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