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Метод функций Грина в задаче о преобразовании случайного сигнала линейной динамической системой

Authors: Khatskevich, V.L.; Makhinova, O.A.;

Метод функций Грина в задаче о преобразовании случайного сигнала линейной динамической системой

Abstract

Владимир Львович Хацкевич, доктор технических наук, профессор, кафедра математики, Военно-Воздушная академия им. проф. Н.Е.Жуковского и Ю.А. Гагарина (г. Воронеж, Российская Федерация), vlkhats@mail.ru. Ольга Алексеевна Махинова, кандидат физико-математических наук, доцент, кафедра математики, Военно-Воздушная академия им. проф. Н.Е. Жуковского и Ю.А. Гагарина (г. Воронеж, Российская Федерация), olga.maxinova@list.ru. Рассматривается динамическая система, описываемая линейным дифференциальным уравнением высокого порядка с постоянными коэффициентами. Методом функций Грина установлена зависимость между числовыми характеристиками случайного сигнала на входе и выходе динамической системы, а именно между математическими ожиданиями и между корреляционными функциями. В отличие от известных результатов, не предполагается стационарность входного и выходного случайных сигналов. A dynamic system is considered, which is described by a high order linear differential equation with constant coefficients. The Green’s function method established the relationship between the numerical characteristics of a random signal at the input and output of a dynamic system, namely between mathematical expectations and between correlation functions. In contrast to the known results, the stationarity of the input and output random signals is not assumed.

Keywords

корреляционные функции, динамические системы со случайными функциями, УДК 681.5.015, correlation functions, dynamical systems with random functions, математические ожидания, непрерывные случайные процессы, mathematical expectations, continuous random processes

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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
Average
Average
Green