Pseudo-random Number Generators

2016 ◽  
pp. 183-195
Author(s):  
Benjamin A. Stickler ◽  
Ewald Schachinger
Keyword(s):  
Random Number ◽  
Random Number Generators ◽  
Pseudo Random Number

Hardware implementation of pseudo-random number generators based on chaotic maps

2017 ◽  
Vol 90 (3) ◽  
pp. 1661-1670 ◽  
Author(s):  
Luis Gerardo de la Fraga ◽  
Esteban Torres-Pérez ◽  
Esteban Tlelo-Cuautle ◽  
Cuauhtemoc Mancillas-López
Keyword(s):  
Hardware Implementation ◽  
Random Number ◽  
Chaotic Maps ◽  
Random Number Generators ◽  
Pseudo Random Number

scholarly journals Problem of uniqueness in the renewal process generated by the uniform distribution

1992 ◽  
Vol 5 (4) ◽  
pp. 291-305 ◽  
Author(s):  
D. Ugrin-Šparac
Keyword(s):  
Integral Representation ◽  
Uniform Distribution ◽  
Gamma Function ◽  
Renewal Process ◽  
Random Number ◽  
Discrete Distribution ◽  
Inverse Image ◽  
Random Number Generators ◽  
Pseudo Random Number

The renewal process generated by the uniform distribution, when interpreted as a transformation of the uniform distribution into a discrete distribution, gives rise to the question of uniqueness of the inverse image. The paper deals with a particular problem from the described domain, that arose in the construction of a complex stochastic test intended to evaluate pseudo-random number generators. The connection of the treated problem with the question of a unique integral representation of Gamma-function is also mentioned.

scholarly journals Influence of Experiment Design in GPA Investigating with Respect to PRNGs

MENDEL ◽  
2018 ◽  
Vol 24 (2) ◽  
Author(s):  
Tomas Brandejsky
Keyword(s):  
Genetic Programming ◽  
Random Number ◽  
Experiment Design ◽  
Parallel Execution ◽  
Random Number Generators ◽  
Pseudo Random Number ◽  
Programming Algorithms

This paper analyses the influence of experiment parameters onto the reliability of experiments with genetic programming algorithms. The paper is focused on the required number of experiments and especially on the influence of parallel execution which affect not only the order of thread execution but also behaviors of pseudo random number generators, which frequently do not respect recommendation of C++11 standard and are not implemented as thread safe. The observations and the effect of the suggested improvements are demonstrated on results of 720,000 experiments.

scholarly journals Robust Pseudo-Random Number Generators with Input Secure Against Side-Channel Attacks

2015 ◽  
pp. 635-654 ◽  
Author(s):  
Michel Abdalla ◽  
Sonia Belaïd ◽  
David Pointcheval ◽  
Sylvain Ruhault ◽  
Damien Vergnaud
Keyword(s):  
Random Number ◽  
Side Channel ◽  
Side Channel Attacks ◽  
Random Number Generators ◽  
Pseudo Random Number

scholarly journals Sponge-Based Pseudo-Random Number Generators

2010 ◽  
pp. 33-47 ◽  
Author(s):  
Guido Bertoni ◽  
Joan Daemen ◽  
Michaël Peeters ◽  
Gilles Van Assche
Keyword(s):  
Random Number ◽  
Random Number Generators ◽  
Pseudo Random Number

Pseudo-random number generators

2003 ◽  
pp. 211-230
Author(s):  
Graham Everest ◽  
Alf van der Poorten ◽  
Igor Shparlinski ◽  
Thomas Ward
Keyword(s):  
Random Number ◽  
Random Number Generators ◽  
Pseudo Random Number
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