Functional synthesis using discrete particle swarm optimization

  • Bambang A.B. Sarif
  • , Mostafa Abd-El-Barr

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Application of multi-valued (non-binary) digital signals can provide considerable relief for a number of problems faced in binary systems, such as increased functional density and interconnection wirings. Heuristics have been used to synthesize Multiple-valued Logic (MVL) functions using near optimal number of product terms. In this paper, we explore the use of particle swarm optimization algorithm for synthesis of MV functions. The proposed approach was tested against 50000 randomly generated 2-variable 4-valued functions. The results show that the proposed algorithm outperforms other deterministic and Ant Colony based approaches in terms of the average number of product terms needed to synthesize a given MVL function.

Original languageEnglish
Title of host publication2008 IEEE Swarm Intelligence Symposium, SIS 2008
DOIs
StatePublished - 2008

Publication series

Name2008 IEEE Swarm Intelligence Symposium, SIS 2008

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering

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