Download e-book for iPad: Anomaly Detection in Random Heterogeneous Media: Feynman-Kac by Martin Simon

By Martin Simon

ISBN-10: 3658109920

ISBN-13: 9783658109929

ISBN-10: 3658109939

ISBN-13: 9783658109936

This monograph is worried with the research and numerical resolution of a stochastic inverse anomaly detection challenge in electric impedance tomography (EIT). Martin Simon reports the matter of detecting a parameterized anomaly in an isotropic, desk bound and ergodic conductivity random box whose realizations are swiftly oscillating. For this goal, he derives Feynman-Kac formulae to carefully justify stochastic homogenization relating to the underlying stochastic boundary price challenge. the writer combines thoughts from the idea of partial differential equations and useful research with probabilistic rules, paving find out how to new mathematical theorems that could be fruitfully utilized in the remedy of the matter to hand. additionally, the writer proposes a good numerical technique within the framework of Bayesian inversion for the sensible resolution of the stochastic inverse anomaly detection challenge.

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Extra resources for Anomaly Detection in Random Heterogeneous Media: Feynman-Kac Formulae, Stochastic Homogenization and Statistical Inversion

Example text

1 Preliminaries For convenience of the reader, let us recall some standard concepts from homogenization theory. , d, denote a vector field. , d. Moreover, we say that φ is divergence-free if for every ψ ∈ Cc∞ (Rd ), d i=1 Rd φi ∂i ψ dx = 0. 1. e. ω ∈ Γ. }. e. e. ω ∈ Γ. 1) defines a stationary random field with respect to the measure P. We call η the potential corresponding to φ. 1. Note that φ ∈ L2pot (Γ) does not imply that {η(x, ω), (x, ω) ∈ Rd × Γ} is a stationary random field with respect to P.

3, the derivation of the Feynman-Kac formulae, is the central part of this chapter. 1 Reflecting diffusion processes In his seminal paper [52], Fukushima established a one-to-one correspondence between regular symmetric Dirichlet forms and symmetric Hunt processes which is the foundation for the construction of stochastic processes via Dirichlet form techniques. Therefore, we assume that the reader is familiar with the theory of symmetric Dirichlet forms, as elaborated for instance in the monographs [54, 115].

The Feynman-Kac semigroup {Ttg , t ≥ 0} is a strong Feller semigroup on L2 (D). 3 Derivation of the Feynman-Kac formulae 45 Proof. 16 that {Ttg , t ≥ 0} is a strongly continuous sub-Markovian contraction semigroup on L2 (D). Ttg is a bounded operator from L1 (D) to L∞ (D) for every t > 0, which can be shown using Fatou’s lemma. e. x, y ∈ D. In order to prove the strong Feller property, we show that Ttg , t > 0, maps bounded Borel functions to C(D). As in the papers [70, 133], we use an iterative method to construct the transition kernel density pg .

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Anomaly Detection in Random Heterogeneous Media: Feynman-Kac Formulae, Stochastic Homogenization and Statistical Inversion by Martin Simon

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