• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Articles
  • Measuring Independence between Statistical Randomness Tests by Mutual Information
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2028
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
News
September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.
September 17, 2026
'I Wish That People Would Place Greater Trust in Science'
When Tatiana Eremicheva chose Fundamental and Computational Linguistics as her field of study, she thought it would be about learning languages. Instead, she discovered it was about helping people. In this interview for the HSE Young Scientists project, she discusses science as a way of understanding the world, billiards as a team-building activity, and why learning to read is not always as easy as it seems.
September 15, 2026
Immunity to Chaos: How Personal Resources Help Us Cope with the Challenges of a Turbulent World
International conflicts, crises and digital overload—the modern world puts our minds to the test every day. Traditional psychology often focuses on the consequences: anxiety, depression, and psychosomatic disorders. But what if we looked at the problem differently—through the lens of the resources that prevent us from breaking down? Psychological immunity is precisely this set of resources. Alena Zolotareva and her group, Psychological Immunity as a Resource for Positive Functioning, are developing an integrative model of this phenomenon, adapting diagnostic tools and preparing for large-scale empirical research. Why do psychologists need to collaborate with medical professionals, and how could their research transform preventive care in clinics and corporations?

 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

Measuring Independence between Statistical Randomness Tests by Mutual Information

Entropy. 2020. Vol. 22. No. 7. Article 741.
Karell-Albo J. A., Legón-Pérez C. M., Madarro-Capó E. J., Rojas O., Sosa Gómez G.
Language: English
DOI
Keywords: mutual informationrandomness testsstatistical independence
Similar publications
Practical Improvement in the Implementation of Two Avalanche Tests to Measure Statistical Independence in Stream Ciphers
Madarro-Capó E. J., Ramos Piñón E. C., Sosa Gómez G., Computation 2024 Vol. 12 No. 3 Article 60
Added: September 18, 2026
Complexity Reduction in Analyzing Independence between Statistical Randomness Tests Using Mutual Information
Karell-Albo J. A., Legón-Pérez C. M., Socorro-Llanes R. et al., Entropy 2023 Vol. 25 No. 11 Article 1545
Added: September 18, 2026
Неявные сообщества в сетях и информационное воздействие
Chepovskiy A., Chepovskiy A., Успехи кибернетики 2025 Т. 6 № 1 С. 55–61
In this paper, the authors study the problem of both assessing the quality of implicit community detection on a graph obtained by importing data from social networks and instant messengers, and methods for analyzing such networks to identify the information impact on its actors. Two approaches to assessing the correctness of dividing a graph into ...
Added: May 23, 2025
The measurement of “interdisciplinarity” and “synergy” in scientific and extra‐scientific collaborations
Leydesdorff L., Ivanova I., Journal of the Association for Information Science and Technology 2021 Vol. 72 No. 4 P. 387–402
Problem solving often requires crossing boundaries, such as those between disciplines. When policy‐makers call for “interdisciplinarity,” however, they often mean “synergy.” Synergy is generated when the whole offers more possibilities than the sum of its parts. An increase in the number of options above the sum of the options in subsets can be measured as ...
Added: October 30, 2020
On the Capacity Estimation of a Slotted Multiuser Communication Channel
Ivanov F., Kreshchuk A., Rybin P. et al., , in: The 11th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2019).: Dublin: IEEE, 2019. P. 1–5.
Added: October 1, 2019
Weighted entropy: basic inequalities
Kelbert M., Suhov Y., Stuhl I., Modern Stochastics: Theory and Applications 2017 Vol. 4 No. 3 P. 233–252
This paper represents an extended version of an earlier note [10]. The concept of weighted entropy takes into account values of different outcomes, i.e., makes entropy contextdependent, through the weight function. We analyse analogs of the Fisher information inequality and entropy power inequality for the weighted entropy and discuss connections with weighted Lieb’s splitting inequality. The concepts of rates ...
Added: October 10, 2017
Connectivity measures applied to human brain electrophysiological data
Ossadtchi A., Journal of Neuroscience Methods 2012 Vol. 207 No. 1 P. 1–16
Connectivity measures are (typically bivariate) statistical measures that may be used to estimate interactions between brain regions from electrophysiological data. We review both formal and informal descriptions of a range of such measures, suitable for the analysis of human brain electrophysiological data, principally electro- and magnetoencephalography. Methods are described in the space–time,space–frequency, and space–time–frequency domains. ...
Added: October 23, 2014
Mutual information spectrum for selection of event-related spatial components. Application to eloquent motor cortex mapping
Pronko P., Baillet S., Pflieger M. et al., Frontiers in Neuroinformatics 2014 Vol. 7
Spatial component analysis is often used to explore multidimensional time series data whose sources cannot be measured directly. Several methods may be used to decompose the data into a set of spatial components with temporal loadings. Component selection is of crucial importance, and should be supported by objective criteria. In some applications, the use of ...
Added: October 23, 2014
The use of mutual information for selection of event-related components in ICA. Application to eloquent motor cortex mapping
Alexei Ossadtchi, Pronko P. K., Baillet S. et al., Frontiers in Neuroinformatics 2014 Vol. 7 No. January P. Article 53
Spatial component analysis is often used to explore multidimensional time series data whose sources cannot be measured directly. Several methods may be used to decompose the data into a set of spatial components with temporal loadings. Component selection is of crucial importance, and should be supported by objective criteria. In some applications, the use of ...
Added: January 29, 2014
Mutual information spectrum for selection of event-related spatial components. Application to eloquent motor cortex mapping
Ossadtchi A., Pronko P. K., Baillet S. et al., Frontiers in Neuroinformatics 2014 Vol. 7 No. 53 P. 1–11
Spatial component analysis is often used to explore multidimensional time series data whose sources cannot be measured directly. Several methods may be used to decompose the data into a set of spatial components with temporal loadings. Component selection is of crucial importance, and should be supported by objective criteria. In some applications, the use of ...
Added: January 19, 2014
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit