Online citations, reference lists, and bibliographies.

Issues Of Quality Assessing Of Stochastic Transformations Results

A O Prokof'ev, Andrey V. Chirkin, Georgiy M. Ivanov
Published 2020 · Computer Science

Cite This
Download PDF
Analyze on Scholarcy
Share
The paper considers methods for generating numerical sequences using deterministic algorithms and their properties. The requirements for various types of pseudorandom sequence generators are presented. Issues of the research of numerical sequences by statistical and graphical methods are considered. An approach to assessing the quality of stochastic transformations results used for information security is described.
This paper references
Metody i sredstva ocenki kachestva generatorov psevdosluchajnyh posledovatel ' nostej , orientirovannyh na reshenie zadach zashhity informacii
V. ChugunkovI. (2012)
10.1109/EICONRUS.2017.7910608
The distribution in space test for quality evaluation of pseudorandom numbers generators
Anton O. Prokofiev (2017)
The Art in Computer Programming
A. Hunt (2001)
10.1109/APEIE.2016.7806399
Research of statistical properties of stochastic calculations using the improved test of distribution on the plane
Ilya V. Chugunkov (2016)
Cryptography and Network Security: Principles and Practice
W. Stallings (1998)
10.1109/EICONRUS.2019.8656654
Methods of Graphical Research of Stochastic Transformation Results
Anton O. Prokofiev (2019)
Application and Assessment of the Quality of Pseudorandom Sequences Generators
M A Ivanov (2012)
Exploring the Limits of Bootstrap
R. Liu (1992)
10.1007/978-1-4757-3860-5
An Introduction to Kolmogorov Complexity and Its Applications
Ming Li (1993)
10.1007/978-3-662-46221-8_16
Probability Theory and Mathematical Statistics
I. Bronshteĭn (1987)
10.1109/EICONRUS.2019.8657165
Development Principles and Classification of PRNG Graphical Tests
Anton O. Prokofiev (2019)
Theory, Application and Assessment of the Quality of Pseudorandom Sequences Generators, Мoscow: NRNU MEPhI
M. A. Ivanov (2012)
10.2307/1402042
Method of statistical testing : Monte Carlo method
D. Kendall (1965)
Testing random number generators, part 2
J. Dwyer (1996)
Random Number Generation and Quasi
Harald Niederreiter (1992)
Kriptograficheskie metody zashchity informatsii v komp'yuternykh sistemakh i setyakh [Cryptographic Methods of Information Defense in the Computer Systems and Networks: Teaching Guide] Мoscow
M. A. Ivanov (2012)
Introduction to operations research
A. Kaufmann (1968)
10.1137/1.9781611970319
The jackknife, the bootstrap, and other resampling plans
B. Efron (1987)
Random number generation and quasi-monte carlo methods
H. Nmderreiter (1992)
10.1109/EICONRUS.2018.8317104
A method of cryptostability analysis of stochastic transformations, based on the Kohonen self-organizing maps
Anton O. Prokofiev (2018)
10.1145/278008.278019
Don't trust parallel Monte Carlo!
P. Hellekalek (1998)
10.2307/2317055
The art of computer programming. Vol.2: Seminumerical algorithms
D. Knuth (1981)
10.5860/choice.27-0936
Genetic Algorithms in Search Optimization and Machine Learning
D. Goldberg (1988)



Semantic Scholar Logo Some data provided by SemanticScholar