DocumentCode
1640837
Title
A high-quality pseudorandom numbers generator based on twi-layer couple cellular automata
Author
Xia Xuewen ; Li Yuanxiang ; Zhu Jixiang
Author_Institution
Sch. of Comput., Wuhan Univ., Wuhan
fYear
2009
Firstpage
2265
Lastpage
2272
Abstract
This paper proposes a new class of cellular automata, twi-layer couple cellular automata (TLCCA), with specific application to pseudorandom number generation. TLCCA consists of two layer each of which is a one dimensional CA. Two different rules are selected in the lower-layer CA on account of hybrid CA had more complex behavior. The upper-layer CA is divided into two parts. These two parts have a novel neighbourhood, which called couple-structure neighbourhood. By this neighbourhood, two parts in upper layer interplay with each other. ENT test suites are adopted to test the randomness of PRNG. In order to find a stable PRNG, entropy, chi-square and serial correlation coefficient and their variability need to be considered. So a multi-objectives optimization algorithm is proposed. The results of experiment indicate that the TLCCA PRNG can obtain credible random number using no less than 48 cells. The merits of TLCCA PRNG are simpler structure, higher efficiency and better robusticity.
Keywords
cellular automata; correlation methods; entropy; optimisation; random number generation; statistical analysis; ENT test suite; TLCCA PRNG; chi-square method; couple-structure neighbourhood; entropy method; multiobjective optimization algorithm; pseudorandom number generation; serial correlation coefficient; twi-layer couple cellular automata; Automatic testing; Character generation; Content addressable storage; Costs; Field programmable gate arrays; Genetic algorithms; Hardware; Random number generation; Sampling methods; Throughput;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location
Trondheim
Print_ISBN
978-1-4244-2958-5
Electronic_ISBN
978-1-4244-2959-2
Type
conf
DOI
10.1109/CEC.2009.4983222
Filename
4983222
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