Regularized OLS algorithm with fast implementation for training multi-output radial basis function networks
Regularized OLS algorithm with fast implementation for training multi-output radial basis function networks
The paper presents an approach for training
multi-output radial basis function (RBF) networks
by combining subset selection with regularisation. A regularised orthogonal least
squares (ROLS) algorithm is derived, which is
capable of constructing parsimonious networks
that generalise well. A fast implementation of the ROLS algorithm further reduces computational requirements significantly. System identification
is used as an example to demonstrate the effectiveness of this training algorithm.
290-294
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
1995
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Chen, S.
(1995)
Regularized OLS algorithm with fast implementation for training multi-output radial basis function networks.
4th IEE International Conference on Artificial Neural Networks, Cambridge, United Kingdom.
25 - 27 Jun 1995.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The paper presents an approach for training
multi-output radial basis function (RBF) networks
by combining subset selection with regularisation. A regularised orthogonal least
squares (ROLS) algorithm is derived, which is
capable of constructing parsimonious networks
that generalise well. A fast implementation of the ROLS algorithm further reduces computational requirements significantly. System identification
is used as an example to demonstrate the effectiveness of this training algorithm.
Text
c-icann1995
- Author's Original
More information
Published date: 1995
Additional Information:
4th IEE International Conference on Artificial Neural Networks (Cambridge, UK), June 26-28, 1995. Event Dates: June 26-28, 1995 Organisation: IEE
Venue - Dates:
4th IEE International Conference on Artificial Neural Networks, Cambridge, United Kingdom, 1995-06-25 - 1995-06-27
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 251087
URI: http://eprints.soton.ac.uk/id/eprint/251087
PURE UUID: 78821ffa-8e3a-4230-bede-e36e15fa1794
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Date deposited: 12 Oct 1999
Last modified: 03 Feb 2022 17:48
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Author:
S. Chen
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