Inverse Modeling 2015
An introduction to the theory and methods of inverse problems and data assimilation
Published on 31. December 2015
506 pages
978-0-7503-1218-9 (ISBN)
Description
This book provides a comprehensive introduction to the techniques, tools and methods for inverse problems and data assimilation, and is written at the interface between mathematics and applications for students, researchers and developers in mathematics, physics, engineering, acoustics, electromagnetics, meteorology, biology, environmental and other applied sciences. Basic analytic questions and tools are introduced, as well as a wide variety of concepts, methods and approaches to formulate and solve inverse problems. OCTAVE /MATLAB® codes are included, which serve as a first step towards simulations and more sophisticated inversion or data assimilation algorithms.
More details
Series
Language
English
Place of publication
Bristol
United Kingdom
Target group
College/higher education
Edition type
Enhanced edition
Illustrations
black and whites and colour
ISBN-13
978-0-7503-1218-9 (9780750312189)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Gen Nakamura | Roland Potthast
Inverse Modeling
An introduction to the theory and methods of inverse problems and data assimilation
Book
12/2015
IOP Publishing Ltd
€153.50
Shipment within 10-20 days
Gen Nakamura | Roland Potthast
Inverse Modeling
An introduction to the theory and methods of inverse problems and data assimilation
Book
12/2015
Institute of Physics Publishing
€50.95
No shipping information available
Persons
Gen Nakamura is currently Harim Professor at Inha University, S. Korea, and Professor Emeritus of Hokkaido University, Japan.
Roland Potthast currently leads the division for data assimilation at the German Meteorological Service, Frankfurt/Offenbach, with a part-time professorship in mathematics at the University of Reading, UK.
Content
1 Introduction 2 Functional analytic tools 3 Approaches to regularization 4 A stochastic view of inverse problems 5 Dynamical systems inversion and data assimilation 6 Programming of numerical algorithms and useful tools 7 Neural field inversion and kernel reconstruction 8 Simulation of waves and fields 9 Nonlinear operators 10 Analysis: uniqueness, stability and convergence questions 11 Source reconstruction and magnetic tomography 12 Field reconstruction techniques 13 Sampling methods 14 Probe methods 15 Analytic continuation tests 16 Dynamical sampling and probe methods 17 Targeted observations and meta-inverse problems
