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NeuroCOLT
Technical Report NC-TR-96-015
Vapnik-Chervonenkis
Dimension of Neural Nets
Wolfgang
Maass
Institute for Theoretical Computer Science
Technische Universitaet Graz
Austria
Abstract
We will survey in this article the most important known bounds for
the VC-dimension of neural nets that consist of linear threshold gates
(section 2) and for the case of neural nets with real-valued activation
functions (section 3). In section 4 we discuss a generalization of
the VC-dimension for neural nets with non-boolean network-output.
With regard to a discussion of the VC-dimension of models for networks
of spiking neurons we refer to Maass (1994).
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Postscript
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