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Optimal solutions for inclusions of geometric brownian motion type with mean derivatives brownian motion type with mean derivatives

Authors: Gliklikh, Yu. E.; Zheltikova, O. O.;

Optimal solutions for inclusions of geometric brownian motion type with mean derivatives brownian motion type with mean derivatives

Abstract

The idea of mean derivatives of stochastic processes was suggested by E. Nelson in 60-th years of XX century. Unlike ordinary derivatives, the mean derivatives are well-posed for a very broad class of stochastic processes and equations with mean derivatives naturally arise in many mathematical models of physics (in particular, E. Nelson introduced the mean derivatives for the needs of Stochastic Mechanics, a version of quantum mechanics). Inclusions with mean derivatives is a natural generalization of those equations in the case of feedback control or in motion in complicated media. The paper is devoted to a brief introduction into the theory of equations and inclusions with mean derivatives and to investigation of a special type of such inclusions called inclusions of geometric Brownian motion type. The existence of optimal solutions maximizing a certain cost criterion, is proved. Идея производных в среднем стохастических процессов была предложена Э. Нельсоном в 60-х годах ХХ века. В отличие от обычных производных, производные в среднем корректно определены для очень широкого класса случайных процессов, и уравнения с производными в среднем естественно возникают во многих математических моделях физики (в частности, Э. Нельсон ввел производные в среднем для нужд Стохастической Механики – варианта квантовой механики). Включения с производными в среднем являются естественными обобщениями указанных уравнений в случае управления с обратной связью или движения в сложных средах. Статья посвящена краткому введению в теорию уравнений и включений с производными в среднем и изучению специального класса подобных включений, называемых включениями типа геометрического броуновского движения. Доказано существование оптимального решения, максимизирующего некоторый функционал качества. Yu.E. Gliklikh, Voronezh State University, Voronezh, Russian Federation, yeg@math.vsu.ru, O.O. Zheltikova, Voronezh State University, Voronezh, Russian Federation, ksu_ola@mail.ru Юрий Евгеньевич Гликлих, доктор физико-математических наук, профессор, кафедра алгебры и топологических методов анализа, Воронежский государственный университет (г. Воронеж, Российская Федерация), yeg@math.vsu.ru. Ольга Олеговна Желтикова, Воронежский государственный университет (г. Воронеж, Российская Федерация), ksu_ola@mail.ru.

Country
Russian Federation
Keywords

stochastic differential inclusions, УДК 519.216.2, mean derivatives, optimal solution, производные в среднем, ГРНТИ 27.47, оптимальное решение, УДК 517.9, стохастические дифференциальные включения, УДК 519.245

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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!
0
Average
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