Optimization and Regularization for Computational Inverse Problems and Applications - Image 1

£70.20

Springer Optimization and Regularization for Computational Inverse Problems and Applications

Name: Optimization and Regularization for Computational Inverse Problems and Applications
Brand: Springer
Price: 70.2 GBP
Availability: InStock

Technical

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Description

"Optimization and Regularization for Computational Inverse Problems and Applications" focuses on advances in inversion theory and recent developments with practical applications, particularly emphasizing the combination of optimization and regularization for solving inverse problems. This book covers both the methods, including standard regularization theory, Fejer processes for linear and nonlinear problems, the balancing principle, extrapolated regularization, nonstandard regularization, nonlinear gradient method, the nonmonotone gradient method, subspace method and Lie group method; and the practical applications, such as the reconstruction problem for inverse scattering, molecular spectra data processing, quantitative remote sensing inversion, seismic inversion using the Lie group method, and the gravitational lensing problem. Scientists, researchers and engineers, as well as graduate students engaged in applied mathematics, engineering, geophysics, medical science, image processing, remote sensing and atmospheric science will benefit from this book. Dr. Yanfei Wang is a Professor at the Institute of Geology and Geophysics, Chinese Academy of Sciences, China. Dr. Sc. Anatoly G. Yagola is a Professor and Assistant Dean of the Physical Faculty, Lomonosov Moscow State University, Russia. Dr. Changchun Yang is a Professor and Vice Director of the Institute of Geology and Geophysics, Chinese Academy of Sciences, China.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3642137415
Category: Books > Subjects > Reference > Writing > Technical
Domain: Amazon UK
Release Date: 04 January 2011
Listed Since: 01 June 2010

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Springer Optimization and Regularization for Computational Inverse Problems and Applications

About as cheap as it gets. The only time it was cheaper was 1 month ago.

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