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Acoustic Tomography Problem with Memory Научная публикация

Журнал Differential Equations
ISSN: 0012-2661 , E-ISSN: 1608-3083
Вых. Данные Год: 2026, Том: 62, Номер: 2, Страницы: 273-281 Страниц : 9 DOI: 10.1134/s0012266126020059
Ключевые слова acoustic tomography, equation with memory, X-ray tomography, stability
Авторы Romanov V.G. 1
Организации
1 Sobolev Institute of Mathematics, Novosibirsk, 630090, Russia

Информация о финансировании (1)

1 Институт математики им. С.Л. Соболева СО РАН FWNF-2022-0009

Реферат: —A system of acoustic equations in which the Lam´e parameter has a memory (i.e., depends on the history) is considered. The dependence has a specific form and is described by an integral convolution operator whose kernel is the product of two functions, one depending on the space coordinates and the other, on time. For this system of equations, we study an acoustic tomography problem in which three functions, namely, the speed of acoustic waves, the medium density, and the component of the memory kernel depending on the space variables, should be reconstructed. To solve this problem, we use information on a series of solutions of direct problems for the acoustic equations with point sources. This information is given for a finite time interval at the points of some sphere inside which the coefficients to be recovered are assumed to be unknown. We show that the problem in question can be reduced to the inverse kinematic problem for reconstructing the speed of sound and two X-ray tomography problems to be solved consecutively.
Библиографическая ссылка: Romanov V.G.
Acoustic Tomography Problem with Memory
Differential Equations. 2026. V.62. N2. P.273-281. DOI: 10.1134/s0012266126020059 WOS Scopus РИНЦ OpenAlex
Оригинальная: Романов В.Г.
Задача акустической томографии с памятью
Дифференциальные уравнения. 2026. Т.62. №2. С.175-185. DOI: 10.7868/S3034503026020038 РИНЦ
Даты:
Поступила в редакцию: 12 янв. 2026 г.
Принята к публикации: 22 янв. 2026 г.
Опубликована в печати: 20 авг. 2026 г.
Опубликована online: 20 авг. 2026 г.
Идентификаторы БД:
≡ Web of science: WOS:001854309400009
≡ Scopus: 2-s2.0-105048108787
≡ РИНЦ: 91954692
≡ OpenAlex: W7203834512
Альметрики: