Lq(Lp) theory and Hölder estimates for parabolic SPDEs

Kyeong Hun Kim

doi:10.1016/j.spa.2004.07.004

L_q(L_p) theory and Hölder estimates for parabolic SPDEs

Kyeong Hun Kim

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

Hölder estimates are given for the solutions of parabolic stochastic partial differential equations in C¹ domains. Also existence and uniqueness theorems are presented in L_p-spaces with weights. It is allowed that the powers of summability with respect to space and time to be different.

Original language	English
Pages (from-to)	313-330
Number of pages	18
Journal	Stochastic Processes and their Applications
Volume	114
Issue number	2
DOIs	https://doi.org/10.1016/j.spa.2004.07.004
Publication status	Published - 2004 Dec
Externally published	Yes

Keywords

Hölder estimate
Stochastic partial differential equations

ASJC Scopus subject areas

Statistics and Probability
Modelling and Simulation
Applied Mathematics

Access to Document

10.1016/j.spa.2004.07.004

Cite this

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title = "Lq(Lp) theory and H{\"o}lder estimates for parabolic SPDEs",

abstract = "H{\"o}lder estimates are given for the solutions of parabolic stochastic partial differential equations in C1 domains. Also existence and uniqueness theorems are presented in Lp-spaces with weights. It is allowed that the powers of summability with respect to space and time to be different.",

keywords = "H{\"o}lder estimate, Stochastic partial differential equations",

author = "Kim, {Kyeong Hun}",

year = "2004",

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journal = "Stochastic Processes and their Applications",

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AB - Hölder estimates are given for the solutions of parabolic stochastic partial differential equations in C1 domains. Also existence and uniqueness theorems are presented in Lp-spaces with weights. It is allowed that the powers of summability with respect to space and time to be different.

KW - Hölder estimate

KW - Stochastic partial differential equations

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DO - 10.1016/j.spa.2004.07.004

M3 - Article

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VL - 114

SP - 313

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JO - Stochastic Processes and their Applications

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