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Keywords:

  • multiple-valued logic;
  • clonal selection algorithm;
  • minimization;
  • chaos

Abstract

In this paper, a chaotic clonal selection algorithm (CCSA) is proposed to synthesize multiple-valued logic (MVL) functions. The MVL function is realized in a multiple-valued sum-of-products expression where product is indicated by MIN and sum by TSUM. The proposed CCSA, in which chaos is incorporated into the clonal selection algorithm to initialize antibodies and maintain the population diversity, is utilized to learn a given target MVL truth table. Furthermore, an adaptive length strategy of antibodies is also introduced to reduce the computational complexity, whereas an improved affinity function enables the algorithm to find less product terms for an MVL function. Simulation results based on a large number of MVL functions demonstrate the efficiency of the proposed method when compared with other traditional methodologies. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.