Optimization and regularization for computationalinverse problems and applications

Optimization and regularization for computationalinverse problems and applications

Wang, Yanfei
Yagola, Anatoly G.
Yang, Changchun

93,55 €(IVA inc.)

'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 spectradata 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 aProfessor 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." First book relating the inversion theory and recent developments with real applications Combines optimization and regularization for solving inverse problems Covers frontiers on multi-disciplinary subjects areas INDICE: Introduction.- Regularization Theory and Recent Developments.- Nonstandard Regularization and Advanced Optimization Theory and Methods.- Numerical Inversion in Geoscience and Quantitative Remote Sensing.

  • ISBN: 978-3-642-13741-9
  • Editorial: Springer
  • Encuadernacion: Cartoné
  • Páginas: 400
  • Fecha Publicación: 01/10/2010
  • Nº Volúmenes: 1
  • Idioma: Inglés