Moreira Numerical Methods for Inverse Problems

Erscheinungsjahr 2020
ISBN: 978-1-77407-910-2
Verlag: Arcler Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 342 Seiten, Electronic book text, Format (B × H): 152 mm x 229 mm

The book Numerical Methods for Inverse Problems consists of contemporaneouss articles featuring not only several well-known inverse problems used in the inference of many physical and engineering systems such as that of the partial differential equations but also the statistical and imaging inverse problems. It includes a variety of numerical methods for solving inverse problems such as that of the Tikhonov regularization; finite differences; and orthogonal decomposition; as well as those based on Bayesian inference, artificial neural networks, and quantum annealing.

Autoren/Hrsg.

Moreira, Olga

Fachgebiete

• Mathematik | Informatik Mathematik Mathematische Analysis Moderne Anwendungen der Analysis

Inhaltsverzeichnis

- Chapter 1: A Numerical Approximation Method for the Inverse Problem of the Three-Dimensional Laplace Equation
- Chapter 2: The numerical solution of forward and inverse Robin problems for Laplace's equation
- Chapter 3: Moving Least Squares Method Fo A One-dimensional Parabolic Inverse Problem
- Chapter 4: The Inverse Problem Of The Heat Equation With Periodic Boundary And Integral Overdetermination Condition
- Chapter 5: An Inverse Problem for a Two-Dimensional Time-Fractional Sideways Heat Equation
- Chapter 6: Numerical Inversion For The Multiple Fractional Orders In The Multiterm TFDE
- Chapter 7: Solutions of Direct and Inverse Even-Order Sturm-Liouville Problems Using Magnus Expansion
- Chapter 8: Numerical Solution of Direct and Inverse Problems for Time-Dependent Volterra Integro-Differential Equation Using Finite Integration Method with Shifted Chebyshev Polynomials
- Chapter 9: Direct And Inverse Problem For Geometric Perturbation Of The Laplace Operator In A Strip
- Chapter 10: Solving Large-Scale Inverse Magnetostatic Problems using the Adjoint Method
- Chapter-11: The problem of the inverse Lyapunov exponent and its applications
- Chapter-12: Nonlinear Damping Identification in Nonlinear Dynamic System Based on Stochastic Inverse Approach
- Chapter-13: Model order reduction for Bayesian approach to inverse problems
- Chapter-14: Statistical Approaches to the Inverse Problem

Über Autor(innen)

Olga Moreira is a Ph.D. in Astrophysics and B.Sc. in Physics and Applied Mathematics. She is an experienced technical writer and researcher which former fellowships include postgraduate positions at two of the most renown European institutions in the fields of Astrophysics and Space Science (the European Southern Observatory, and the European Space Agency). Presently, she is an independent scientist working on projects involving machine learning and neural networks research as well as peer-reviewing and edition of academic books.