Published In

Kybernetes

Document Type

Post-Print

Publication Date

2004

Subjects

Reconstructability Analysis, Information Theory, Probabilistic graphical modeling, Multivariate analysis discrete multivariate modeling, Data mining

Abstract

Modified reconstructability analysis (MRA), a novel decomposition technique within the framework of set‐theoretic (crisp possibilistic) reconstructability analysis, is applied to three‐variable NPN‐classified Boolean functions. MRA is superior to conventional reconstructability analysis, i.e. it decomposes more NPN functions. MRA is compared to Ashenhurst‐Curtis (AC) decomposition using two different complexity measures: log‐functionality, a measure suitable for machine learning, and the count of the total number of two‐input gates, a measure suitable for circuit design. MRA is superior to AC using the first of these measures, and is comparable to, but different from AC, using the second.

Description

Authors' version of an article which subsequently appeared in Kybernetes, published by Emerald Group Publishing Limited. The version of record may be found at http://dx.doi.org/10.1108/03684920410533985.

DOI

10.1108/03684920410533985

Persistent Identifier

http://archives.pdx.edu/ds/psu/16499

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