Innovative Approach to Generate Uniform Random Numbers Based on a Novel Cellular Automata

2009 ◽  
Vol 9 (22) ◽  
pp. 4071-4075 ◽  
Author(s):  
R. Ayanzadeh ◽  
K. Hassani ◽  
Y. Moghaddas ◽  
H. Gheiby ◽  
S. Setayeshi
1996 ◽  
Vol 07 (02) ◽  
pp. 181-190 ◽  
Author(s):  
MOSHE SIPPER ◽  
MARCO TOMASSINI

Random numbers are needed in a variety of applications, yet finding good random number generators is a difficult task. In this paper non-uniform cellular automata (CA) are studied, presenting the cellular programming algorithm for co-evolving such CAs to perform computations. The algorithm is applied to the evolution of random number generators; our results suggest that evolved generators are at least as good as previously described CAs, with notable advantages arising from the existence of a "tunable" algorithm for obtaining random number generators.


Author(s):  
A.F. Deon ◽  
V.A. Onuchin ◽  
Yu.A. Menyaev

Various pseudorandom number generation algorithms may be used to create a discrete stochastic plane. If a Cartesian completeness property is required of the plane, it must be uniform. The point is, employing the concept of uncontrolled random number generation may yield low-quality results, since original sequences may omit random numbers or not be sufficiently uniform. We present a novel approach for generating stochastic Cartesian planes according to the model of complete twister sequences featuring uniform random numbers without omissions or repetitions. Simulation results confirm that the random planes obtained are indeed perfectly uniform. Moreover, recombining the original complete uniform sequence parameters allows the number of planes created to be significantly increased without using any extra random access memory.


2000 ◽  
Vol 49 (10) ◽  
pp. 1146-1151 ◽  
Author(s):  
M. Perrenoud ◽  
M. Sipper ◽  
M. Tomassini

1983 ◽  
pp. 180-213
Author(s):  
Paul Bratley ◽  
Bennett L. Fox ◽  
Linus E. Schrage

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