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Theory of Probability and Mathematical Statistics

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Linear equations and stochastic exponents in a Hilbert space


Authors: Yuliya Mishura and Georgiy Shevchenko
Translated by: G. Shevchenko
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 71 (2004).
Journal: Theor. Probability and Math. Statist. 71 (2005), 139-149
MSC (2000): Primary 60H10; Secondary 34G10, 47A50, 47D06
Published electronically: December 30, 2005
MathSciNet review: 2144327
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Abstract | References | Similar Articles | Additional Information

Abstract: We consider linear stochastic differential equations in a Hilbert space and obtain general limit theorems. As a corollary, we get a result on the convergence of finite-dimensional approximations of solutions of such equations.


References [Enhancements On Off] (What's this?)

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Additional Information

Yuliya Mishura
Affiliation: Chair of Probability Theory and Mathematical Statistics, Department of Mechanics and Mathematics, Kyiv National Taras Shevchenko University, Glushkov pr. 6, Kyiv 03127, Ukraine
Email: myus@univ.kiev.ua

Georgiy Shevchenko
Affiliation: Chair of Probability Theory and Mathematical Statistics, Department of Mechanics and Mathematics, Kyiv National Taras Shevchenko University, Glushkov pr. 6, Kyiv 03127, Ukraine
Email: zhora@univ.kiev.ua

DOI: https://doi.org/10.1090/S0094-9000-05-00654-X
Keywords: Linear stochastic differential equation, stochastic exponent
Received by editor(s): December 18, 2002
Published electronically: December 30, 2005
Additional Notes: The second author is partially supported by INTAS grant YSF 03-55-2447.
Article copyright: © Copyright 2005 American Mathematical Society