FlexNet - a flexible neural network construction algorithm

[Karim Mohraz]

The following paper is available via WWW

          FlexNet - a flexible neural network construction algorithm

Abstract
Dynamic neural network algorithms are used for automatic network
design in order to avoid time consuming search for finding an 
appropriate network topology with trial & error methods. The new 
FlexNet algorithm, unlike other network construction algorithms, 
does not underlie any constraints regarding the number of hidden 
layers and hidden units. In addition different connection strategies 
are available, together with candidate pool training and the option of
freezing weights. Test results on 3 different benchmarks showed higher
generalization rates for FlexNet compared to Cascade-Correlation and 
optimized MLP networks.

Keywords: network construction, generalization, Cascade-Correlation.

This paper has been accepted for publication in the European Symposium on
Artificial Neural Networks (ESANN), Bruges, Belgium , April, 96.

 http://www.physik.uni-marburg.de/bio/mitarbei/karim/flexnet.ps

(6 pages)
Sorry, no hardcopies available



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Karim Mohraz			     Bereich Neuronale Netze & Fuzzy Logik         
			  Bayerisches Forschungszentrum fuer Wissensbasierte Systeme
					    F O R W I S S  Erlangen

New address:		          AG Neurophysik, Universitaet Marburg, Germany

Email: karim at bio.physik.uni-marburg.de
WWW:   http://www.physik.uni-marburg.de/bio/mitarbei/karim.html

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