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Minimization of incompletely specified mixed polarity Reed Muller functions using genetic algorithm.

Al-Jassani, ban Adil, Urquhart, Neil B and Almaini, A E A (2009) Minimization of incompletely specified mixed polarity Reed Muller functions using genetic algorithm. In: 3rd IEEE international conference on Signal Circuits and Systems, 2009 November, Tunis.

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Abstract/Description

A New and efficient Genetic Algorithm (GA) based approach is presented to minimise the number of terms of Mixed Polarity Reed Muller (MPRM) single and multi output incompletely specified Boolean functions. The algorithm determines the allocation of don’t care terms for the given function resulting in optimal MPRM expansions. For an n-variable function with ? unspecified minterms there are (3n × 2?) distinct MPRM expansions. A minimum MPRM is one with the fewest products. The algorithm is implemented in C++ and fully tested using standard benchmark examples. For the benchmark examples tested, the number of terms is reduced, on average, by 49% if “don’t care” terms are included.

Item Type: Conference or Workshop Item (Paper)
ISBN: 978-1-4244-4398-7
Uncontrolled Keywords: Mixed Polarity Reed Muller; incompletely specified Boolean functions; aenetic algorithm;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science
000 Computer science, information & general works > 000 Computer science, knowledge & systems > 005 Computer programming, programs & data
Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Item ID: 3500
Depositing User: Computing Research
Date Deposited: 15 Jan 2010 14:23
Last Modified: 26 Jan 2016 13:14
URI: http://researchrepository.napier.ac.uk/id/eprint/3500

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