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Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Печать: 1064-2315
ISSN Онлайн: 2163-9337

Выпуски:
Том 52, 2020 Том 51, 2019 Том 50, 2018 Том 49, 2017 Том 48, 2016 Том 47, 2015 Том 46, 2014 Том 45, 2013 Том 44, 2012 Том 43, 2011 Том 42, 2010 Том 41, 2009 Том 40, 2008 Том 39, 2007 Том 38, 2006 Том 37, 2005 Том 36, 2004 Том 35, 2003 Том 34, 2002 Том 33, 2001 Том 32, 2000 Том 31, 1999 Том 30, 1998 Том 29, 1997 Том 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v51.i11.30
pages 22-33

Recurrent Models of Randomized Processes in Foreign Intelligence Tasks.
Part 2. Simplified High Order Models

Farit F. Idrisov
Tomsk State University of Control Systems and Radioelectronics, Tomsk

Краткое описание

Foreign intelligence at all times has always remained the sphere of special attention of many states. Its significance has particularly increased at the present time in connection with the acute nature of their relationship. New forms of conflicts have appeared: network and hybrid wars, large-scale terrorist acts, the space for their conduct has become more complicated − cyberspace has been added to the traditional maritime, land and air spaces. The development of foreign intelligence tools is a long and expensive process, requiring constant additions and changes in accordance with events in the international arena. However, the use of the theory of random processes for these purposes encounters one very difficult problem. The fact is that the classical theory implies the processing of data under conditions of equidistant observations, while in reality intelligence data is a stream of data obtained at random times. Moreover, a random amount of data may arrive at random times and, finally, there may be a situation where there is so small quantity of intelligence data that it is impossible to draw any conclusions on the decision making. For such very often encountered conditions, spline models of varying degrees of complexity are proposed in the work, which allow synthesizing adaptive algorithms with precisely known and unknown moments of changes in the state of the reconnaissance object. The Poisson process is used as an event flow model. The correctness of the algorithms is ensured by the mathematical rigor of the above reasoning; the results of simulation are presented.

ЛИТЕРАТУРА

  1. Idrisov F.F., Recursive models of randomized processes in foreign intelligence tasks. Part 1. Simplified lower order models, "Mezhdunarodnyi nauchno-tekhnicheskiy zhurnal "Problemy upravleniya i informatiki", 2019, No. 5, 137-149. .

  2. Lifshits K.I., Smoothing experimental data with splines [in Russian], Izdatelstvo Tomskogo universiteta, Tomsk. 1991. .


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