DocumentCode
391748
Title
Information measures in detecting and recognizing symmetries
Author
Popel, Denis V.
Author_Institution
Dept. of Comput. Sci., Baker Univ., Baldwin City, KS, USA
Volume
2
fYear
2002
fDate
4-7 Aug. 2002
Abstract
This paper presents a method to detect and recognize symmetries in Boolean functions. The idea is to use information theoretic measures of Boolean functions to detect sub-space of possible symmetric variables. Coupled with the new techniques of efficient estimations of information measures on Binary Decision Diagrams (BDDs) we obtain promised results in symmetries detection for large-scale functions.
Keywords
Boolean functions; binary decision diagrams; information theory; symmetry; Boolean function; binary decision diagram; information theoretic measure; symmetry detection; symmetry recognition; Boolean functions; Cities and towns; Computer science; Data structures; Entropy; Galois fields; Large-scale systems; Logic design; Logic testing; Probability distribution;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2002. MWSCAS-2002. The 2002 45th Midwest Symposium on
Print_ISBN
0-7803-7523-8
Type
conf
DOI
10.1109/MWSCAS.2002.1186860
Filename
1186860
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