Permutation entropy as a tool for analyzing noise-like time series

2020 ◽  
Author(s):  
Victor Panchelyuga ◽  
A. Lapshin
Keyword(s):  
Time Series ◽  
Distribution Function ◽  
Random Number ◽  
Random Number Generator ◽  
Alpha Decay ◽  
Permutation Entropy ◽  
Number Generator ◽  
High Quality ◽  
The Subject ◽  
Very High

The subject of this work is the study of time series of fluctuations or noise-like time series. Very often, such time series are considered as a standard of randomness. For example, time series of alpha decay rate fluctuations are commonly used as a very high quality random number generator. It is believed that locally such time series are completely random and do not carry any information. Therefore, the main methods of their research are global, for example, the distribution function.

scholarly journals High Quality FPGA Optimized Random Number Generator

2013 ◽  
Vol 67 (17) ◽  
pp. 1-4 ◽  
Author(s):  
V. NavyaDeepthi ◽  
A. Ruhan Bevi ◽  
V. Sai Keerthi
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
High Quality

scholarly journals RANDOM NUMBER GENERATOR BASED ON HUMAN-COMPUTER INTERACTION

2020 ◽  
pp. 17-23
Author(s):  
A. S. Averin ◽  
◽  
N. D. Zyulyarkina ◽  
E. M. Izhberdeeva ◽  
◽  
...  
Keyword(s):  
Distribution Function ◽  
Human Computer Interaction ◽  
Preliminary Analysis ◽  
Random Number ◽  
Random Number Generator ◽  
Random Numbers ◽  
Number Generator ◽  
Number Distribution ◽  
Computer Interaction

The paper is devoted to the development and analysis of a software random number gen-erator based on human-computer interaction for software and cryptographic applications. De-scribed is a method of generating random numbers based on human-computer interaction, using time and position of a cursor on a computer or smartphone display. Based on this meth-od, a random number generator has been developed and programmatically implemented. A preliminary analysis of the algorithm was performed, during which 11,000 numbers were gen-erated. The test software for this method has been created, preliminary indicators of generated random numbers have been considered. The random number distribution function is shown to be uniform. The advantage of this generator is its ease of manufacture and operation

STATISTICAL TESTING OF A CHAOS BASED CMOS TRUE-RANDOM NUMBER GENERATOR

2010 ◽  
Vol 19 (04) ◽  
pp. 897-910 ◽  
Author(s):  
FABIO PARESCHI ◽  
GIANLUCA SETTI ◽  
RICCARDO ROVATTI
Keyword(s):  
Random Number ◽  
Piecewise Linear ◽  
Random Number Generator ◽  
Statistical Testing ◽  
Number Generator ◽  
High Quality ◽  
True Random Number Generator ◽  
Power Of The Test ◽  
Depth Analysis ◽  
Randomness Tests

As faster Random Number Generators become available, the possibility to improve the accuracy of randomness tests through the analysis of a larger number of generated bits increases. In this paper we first introduce a high-performance true-random number generator designed by authors, which use a set of discrete-time piecewise-linear chaotic maps as its entropy source. Then, we present by means of suitably improved randomness tests, the validation of this generator and the comparison with other high-end solutions. We consider the NIST test suite SP 800-22 and we show that, as suggested by NIST itself, to increase the so-called power of the test, a more in-depth analysis should be performed using the outcomes of the suite over many generated sequences. With this approach we build a framework for RNG high quality testing, with which we are able to show that the designed prototype has a comparable quality with respect to the other high-quality commercial solutions, with a working speed that is one order of magnitude faster.

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