Bayesian parameter identification in impedance boundary conditions for Helmholtz problems
DOI10.1137/23m1591517zbMATH Open1547.35207MaRDI QIDQ6573175
Reinhild Roden, Nick Wulbusch, A. A. Chernov, Matthias Blau
Publication date: 16 July 2024
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
finite element methodMonte Carlo methodHelmholtz equationBayesian inverse problemsacoustic impedance
Bayesian inference (62F15) Monte Carlo methods (65C05) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Laplace operator, Helmholtz equation (reduced wave equation), Poisson equation (35J05) PDEs with randomness, stochastic partial differential equations (35R60) Numerical methods for inverse problems for boundary value problems involving PDEs (65N21)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Application of quasi-Monte Carlo methods to elliptic PDEs with random diffusion coefficients: a survey of analysis and implementation
- Multi-level Monte Carlo finite element method for elliptic PDEs with stochastic coefficients
- Inverse problems: A Bayesian perspective
- Numerical-asymptotic boundary integral methods in high-frequency acoustic scattering
- Multilevel Monte Carlo Path Simulation
- NONLINEAR APPROACH TO APPROXIMATE ACOUSTIC BOUNDARY ADMITTANCE IN CAVITIES
- Low-frequency assessment of thein situ acoustic absorption of materials in rooms: an inverse problem approach using evolutionary optimization
- Finite Element Methods in Local Active Control of Sound
- An application of sparse measure valued Bayesian inversion to acoustic sound source identification
- Quasi-Monte Carlo and Multilevel Monte Carlo Methods for Computing Posterior Expectations in Elliptic Inverse Problems
- Large-scale scientific computing. 3rd international conference, LSSC 2001, Sozopol, Bulgaria, June 6--10, 2001. Revised papers
This page was built for publication: Bayesian parameter identification in impedance boundary conditions for Helmholtz problems