Title :
Information measures in detecting and recognizing symmetries
Author_Institution :
Dept. of Comput. Sci., Baker Univ., Baldwin City, KS, USA
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;
Conference_Titel :
Circuits and Systems, 2002. MWSCAS-2002. The 2002 45th Midwest Symposium on
Print_ISBN :
0-7803-7523-8
DOI :
10.1109/MWSCAS.2002.1186860