Title :
Minimization of incompletely specified mixed polarity reed muller functions using Genetic Algorithm
Author :
Al Jassani, B.A. ; Urquhart, N. ; Almaini, A.E.A.
Author_Institution :
Edinburgh Napier Univ., Edinburgh, UK
Abstract :
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 à unspecified minterms there are (3n à 2Ã) 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.
Keywords :
Boolean functions; genetic algorithms; minimisation; C++; genetic algorithm; incompletely specified Boolean functions; mixed polarity Reed Muller function minimisation; n-variable function; Benchmark testing; Boolean functions; Circuit testing; Circuits and systems; Corporate acquisitions; Genetic algorithms; Logic design; Logic gates; Logic testing; Minimization methods; Genetic Algorithm; Incompletely specified Boolean functions; Mixed Polarity Reed Muller;
Conference_Titel :
Signals, Circuits and Systems (SCS), 2009 3rd International Conference on
Conference_Location :
Medenine
Print_ISBN :
978-1-4244-4397-0
Electronic_ISBN :
978-1-4244-4398-7
DOI :
10.1109/ICSCS.2009.5412318