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Applied Mathematics
Article . 2011 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Improving Middle Square Method RNG Using Chaotic Map

Authors: Hamed Rahimov; Majid Babaie; Hassan Hassanabadi;

Improving Middle Square Method RNG Using Chaotic Map

Abstract

One of the classic approaches in PRNGs is the middle square method in which with a simple mathe-matical model generating pseudorandom numbers in high speed and minimum correlation between output numbers. Despite these unique characteristics, the method contains weaknesses that a broader application of this algo- rithm will face. In this paper is studied middle square method and then a logistic chaotic map is introduced with its specific features and its improved weaknesses via using these characteristics. Finally the NIST tests suite s are presented, in order to detect the specific characteristics expected from truly random sequences.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Top 10%
Average
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