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Anomaly Detection in Random Heterogeneous Media - Feynman-Kac Formulae, Stochastic Homogenization and Statistical Inversion (Paperback, 1st ed. 2015) Loot Price: R1,813
Discovery Miles 18 130
Anomaly Detection in Random Heterogeneous Media - Feynman-Kac Formulae, Stochastic Homogenization and Statistical Inversion...

Anomaly Detection in Random Heterogeneous Media - Feynman-Kac Formulae, Stochastic Homogenization and Statistical Inversion (Paperback, 1st ed. 2015)

Martin Simon

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Loot Price R1,813 Discovery Miles 18 130 | Repayment Terms: R170 pm x 12*

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This monograph is concerned with the analysis and numerical solution of a stochastic inverse anomaly detection problem in electrical impedance tomography (EIT). Martin Simon studies the problem of detecting a parameterized anomaly in an isotropic, stationary and ergodic conductivity random field whose realizations are rapidly oscillating. For this purpose, he derives Feynman-Kac formulae to rigorously justify stochastic homogenization in the case of the underlying stochastic boundary value problem. The author combines techniques from the theory of partial differential equations and functional analysis with probabilistic ideas, paving the way to new mathematical theorems which may be fruitfully used in the treatment of the problem at hand. Moreover, the author proposes an efficient numerical method in the framework of Bayesian inversion for the practical solution of the stochastic inverse anomaly detection problem.

General

Imprint: Springer Spektrum
Country of origin: Germany
Release date: July 2015
First published: 2015
Authors: Martin Simon
Dimensions: 210 x 148 x 10mm (L x W x T)
Format: Paperback
Pages: 150
Edition: 1st ed. 2015
ISBN-13: 978-3-658-10992-9
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
Books > Science & Mathematics > Physics > General
Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Differential equations
Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN: 3-658-10992-0
Barcode: 9783658109929

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