3 research outputs found
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Genetic algorithm approach to find the best input variable partitioning
Conference PaperThis paper presents a variable partition algorithm which combines the quasi-reduced ordered multiple-terminal multiple-valued decision diagrams and genetic algorithms (GAs). The algorithm is better than the previous techniques which find a good functional decomposition by non-exhaustive search and expands the range of searching for the best decomposition providing the optimal subtable multiplicity. The possible solutions are evaluated using the gain of decomposition for a multiple-output multiple-valued logic function. The distinct feature of GA is the possible solutions being coded by real numbers. Here the simplex-based crossover is proposed to use for the recombination stage of GA. It permits to increase the GA coverag
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Using a genetic algorithm for optimizing the functional decomposition of multiple-valued functions
The genetic algorithm which determines the good functional decomposition of multiple-valued logic functions is presented. The algorithm expands the range of searching for a best decomposition, providing the optimal column multiplicity. The possible solutions are evaluated using the gain of decomposition for multiple-valued function