Authors: Žunić, Joviša 
Affiliations: Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: On encoding and enumerating threshold functions
Journal: IEEE Transactions on Neural Networks
Volume: 15
Issue: 2
First page: 261
Last page: 267
Issue Date: 1-Jan-2004
Rank: M21a
ISSN: 1045-9227
DOI: 10.1109/TNN.2004.824419
Abstract: 
In this paper, we deal with encoding and enumerating threshold functions defined on n-dimensional binary inputs. The paper specifies situations in which the unique characterization of functions from a given class is preserved by usage of an appropriate set of discrete moments. Moreover, sometimes such a characterization (coding) is optimal with respect to the number of necessary bit rate per coded function. By estimating the number of possible values of the discrete moments used, several upper bounds (for different classes of threshold functions) are derived, some of which are better than those previously known.
Keywords: Discrete moments | Encoding | Enumerating | Neural networks | Threshold functions
Publisher: IEEE

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