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Evolving cellular automata to generate nonlinear sequences with desirable properties

  • Syn Kiat Tan
  • , Sheng Uei Guan*
  • *Corresponding author for this work
  • National University of Singapore
  • Brunel University London

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

This paper presents a new chromosomal representation and associated genetic operators for the evolution of highly nonlinear cellular automata that generate pseudorandom number sequences with desirable properties ensured. This chromosomal representation reduces the computational complexity of genetic operators to evolve valid solutions while facilitating fitness evaluation based on the DIEHARD statistical tests.

Original languageEnglish
Pages (from-to)1131-1134
Number of pages4
JournalApplied Soft Computing
Volume7
Issue number3
DOIs
Publication statusPublished - Jun 2007
Externally publishedYes

Keywords

  • Cellular automata
  • Incremental evolution
  • Random number generation

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