ARTICLE
Thimm-97.5/IDIAP
Two neural network construction methods
Thimm, Georg
Fiesler, Emile
Boolean logic
connectionism
high order neural network
high order perceptron
ontogenic neural network
Neural Processing Letters
6
01
1997
Two low complexity methods for neural network construction, that are applicable to various neural network models, are introduced and evaluated for high order perceptrons. The methods are based on a Boolean approximation of real-valued data. This approximation is used to construct an initial neural network topology which is subsequently trained on the original (real-valued) data. The methods are evaluated for their effectiveness in reducing the network size and increasing the network's generalization capabilities in comparison to fully connected high order perceptrons.