Fast Gaussian random number generation using linear transformations

T. Herendi*, T. Siegl, R. F. Tichy

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We develop a method for generating pseudorandom sequences with Gaussian distribution. The method is based on completely uniformly distributed sequences and linear transformations, such as the Fourier transform and Walsh transform. We obtain some discrepancy estimates and make a numerical comparison of these two transformations. Furthermore, we show how this method can be used for testing randomness. We remark that similar approaches are due to Gut, Egorov and Il'in [7], Yuen [26] and Rader [21].

Original languageEnglish
Pages (from-to)163-181
Number of pages19
Issue number2
Publication statusPublished - 1 Jan 1997


  • Completely uniform distribution
  • Fourier transform
  • Gaussian random number generation
  • Walsh transform

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Numerical Analysis
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


Dive into the research topics of 'Fast Gaussian random number generation using linear transformations'. Together they form a unique fingerprint.

Cite this