Inverse Problems for Stochastic Partial Differential Equations
Category: eBooks
- views: 149
- date: 24 May 2026
- posted by: BeMyLove
Inverse Problems for Stochastic Partial Differential Equations | 3.81 MB
Title: Inverse Problems for Stochastic Partial Differential Equations
Author: Qi Lü · Yu Wang
Category: Nonfiction, Science & Nature, Mathematics, Mathematical Analysis
Language: English | 147 Pages | ISBN: 3540156941
Description:
This book provides a comprehensive and systematic introduction to inverse problems for stochastic partial differential equations (SPDEs), with particular emphasis on stochastic parabolic and hyperbolic equations. It addresses both the unique challenges and new opportunities that arise in the stochastic setting. Key topics include inverse state problems (such as determining unknown initial conditions) and inverse source problems (identifying unknown source terms), with a focus on the mathematical tools essential for their analysis, especially global Carleman estimates tailored to SPDEs. The book explores fundamental issues of uniqueness, stability, and reconstruction under various measurement scenarios, including internal, boundary, and terminal observations. It highlights how stochasticity can fundamentally alter the nature of inverse problems, sometimes enabling solutions where deterministic approaches fail. Reconstruction methods such as Tikhonov regularization are also discussed in detail. This book is intended for graduate students and researchers in applied mathematics, stochastic analysis, and PDEs, as well as practitioners in fields like mathematical finance, physics, and engineering who require rigorous methods for uncertainty quantification. A moderate background in PDEs, functional analysis, and basic stochastic calculus is beneficial.
DOWNLOAD:
https://rapidgator.net/file/69090609fedd2479c673da8c059716cf/Inverse_Problems_for_Stochastic_Partial_Differential_Equations.rar
https://nitroflare.com/view/8BB42438790ECBA/Inverse_Problems_for_Stochastic_Partial_Differential_Equations.rar
This book provides a comprehensive and systematic introduction to inverse problems for stochastic partial differential equations (SPDEs), with particular emphasis on stochastic parabolic and hyperbolic equations. It addresses both the unique challenges and new opportunities that arise in the stochastic setting. Key topics include inverse state problems (such as determining unknown initial conditions) and inverse source problems (identifying unknown source terms), with a focus on the mathematical tools essential for their analysis, especially global Carleman estimates tailored to SPDEs. The book explores fundamental issues of uniqueness, stability, and reconstruction under various measurement scenarios, including internal, boundary, and terminal observations. It highlights how stochasticity can fundamentally alter the nature of inverse problems, sometimes enabling solutions where deterministic approaches fail. Reconstruction methods such as Tikhonov regularization are also discussed in detail. This book is intended for graduate students and researchers in applied mathematics, stochastic analysis, and PDEs, as well as practitioners in fields like mathematical finance, physics, and engineering who require rigorous methods for uncertainty quantification. A moderate background in PDEs, functional analysis, and basic stochastic calculus is beneficial.
DOWNLOAD:
https://rapidgator.net/file/69090609fedd2479c673da8c059716cf/Inverse_Problems_for_Stochastic_Partial_Differential_Equations.rar
https://nitroflare.com/view/8BB42438790ECBA/Inverse_Problems_for_Stochastic_Partial_Differential_Equations.rar
We need your support!
Make a donation to help us stay online
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem
Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u
USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm
Information |
|||
 |
Users of GUESTS are not allowed to comment this publication. | ||