This paper presents a theoretical analysis and some experimental results concerning the effects of both weights and activation function actual implementation, for feedforward multi-layer digital neural networks. The analysis allows us to derive some practical boundaries on the number of bits for the weight representation and on the number of levels for a stepwise approximation of the activation function (however, the analysis can be applied to different implementation technologies). By following such a rules, the equivalence between the abstract neural model and an actual cost-effective VLSI implementation is a priori guaranteed.
Correct Implementation of Digital Neural Networks
FORNACIARI, WILLIAM;SALICE, FABIO
1995-01-01
Abstract
This paper presents a theoretical analysis and some experimental results concerning the effects of both weights and activation function actual implementation, for feedforward multi-layer digital neural networks. The analysis allows us to derive some practical boundaries on the number of bits for the weight representation and on the number of levels for a stepwise approximation of the activation function (however, the analysis can be applied to different implementation technologies). By following such a rules, the equivalence between the abstract neural model and an actual cost-effective VLSI implementation is a priori guaranteed.File | Dimensione | Formato | |
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