Applied statistics algorithms
Computer Generation of Random Variables Using the Ratio of Uniform Deviates
ACM Transactions on Mathematical Software (TOMS)
Computer methods for sampling from the exponential and normal distributions
Communications of the ACM
Algorithm 488: A Gaussian pseudo-random number generator
Communications of the ACM
Fast pseudorandom generators for normal and exponential variates
ACM Transactions on Mathematical Software (TOMS)
Development of a mathematical subroutine library for Fujitsu vector parallel processors
ICS '98 Proceedings of the 12th international conference on Supercomputing
Automatic sampling with the ratio-of-uniforms method
ACM Transactions on Mathematical Software (TOMS)
Overcoming the obstacles of zero-knowledge watermark detection
Proceedings of the 2004 workshop on Multimedia and security
A Gaussian Noise Generator for Hardware-Based Simulations
IEEE Transactions on Computers
Gaussian random number generators
ACM Computing Surveys (CSUR)
A compact and accurate Gaussian variate generator
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A hardware gaussian noise generator using the wallace method
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Local Shannon entropy measure with statistical tests for image randomness
Information Sciences: an International Journal
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A method is presented for generating pseudorandom numbers with a normal distribution. The technique uses the ratio of uniform deviates method discovered by Kinderman and Monahan with an improved set of bounding curves. An optimized quadratic fit reduces the expected number of logarithm evaluations to 0.012 per normal deviate. The method gives a theoretically correct distribution and can be implemented in 15 lines of FORTRAN. Timing and source size comparisons are made with other methods for generating normal deviates. The proposed algorithm compares favorably with some of the better algorithms.