Random sequence generation using clipped hopfield neural network

Choi-Kuen Chan, Chi-Kwong Chan, L. M. Cheng

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 12 - Chapter in an edited book (Author)peer-review

Abstract

A new random sequence generator based on a clipped Hopfield neural network is proposed. Sequences produced by the proposed generator have passed standard statistical tests, exhibiting a good random behavior. By executing the neural network in a parallel architecture in the proposed generator, random outputs of variable length are obtained. The parallel structure of the clipped Hopfield neural network results in fast operation and can easily be implemented using hardware.
Original languageEnglish
Title of host publicationAdvances in Neural Networks and Applications
PublisherWorld Scientific and Engineering Academy and Society
Pages253-255
ISBN (Print)9608052262
Publication statusPublished - 2001

Research Keywords

  • Hardware
  • Hopfield neural network
  • Parallel structure
  • Random sequence generator
  • Statistical tests
  • Variable length

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