Runge-Kutta type regularization method for inversion of spheroidal particle distribution from limited optical data
DOI10.1080/17415977.2013.830615zbMath1304.65174OpenAlexW1986866666MaRDI QIDQ5496493
Lukas Osterloh, Christine Böckmann
Publication date: 2 February 2015
Published in: Inverse Problems in Science and Engineering (Search for Journal in Brave)
Full work available at URL: https://publishup.uni-potsdam.de/frontdoor/index/index/docId/44120
Runge-Kutta methoditerative regularizationinverse scatteringinverse ill-posed problemaerosol particles
Multistep, Runge-Kutta and extrapolation methods for ordinary differential equations (65L06) Numerical methods for inverse problems for integral equations (65R32) Inverse problems (including inverse scattering) in optics and electromagnetic theory (78A46)
Cites Work
- Unnamed Item
- Regularized inversion of microphysical atmospheric particle parameters: theory and application
- The regularizing Levenberg-Marquardt scheme is of optimal order
- Iterative regularization method for lidar remote sensing
- Parallel software for retrieval of aerosol distribution from LIDAR data in the framework of EARLINET-ASOS
- Padé iteration method for regularization
- Computation of the singular value expansion
- The Levenberg-Marquardt method for approximation of solutions of irregular operator equations
- On the convergence of a regularizing Levenberg-Marquardt scheme for nonlinear ill-posed problems
- Convergence rate analysis of the first-stage Runge–Kutta-type regularizations
- Iteration methods for convexly constrained ill-posed problems in hilbert space
- On the asymptotical regularization of nonlinear ill-posed problems
- Runge–Kutta integrators yield optimal regularization schemes
- Computational Methods for Inverse Problems
- Iterative Runge–Kutta-type methods for nonlinear ill-posed problems
This page was built for publication: Runge-Kutta type regularization method for inversion of spheroidal particle distribution from limited optical data