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  • © 2011

Optimization and Regularization for Computational Inverse Problems and Applications

  • 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

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xvii
  2. Introduction

    1. Front Matter

      Pages 1-1
  3. Regularization Theory and Recent Developments

    1. Front Matter

      Pages 15-15
    2. Inverse Problems with A Priori Information

      • Vladimir V. Vasin
      Pages 35-64
    3. Extrapolation Techniques of Tikhonov Regularization

      • Tingyan Xiao, Yuan Zhao, Guozhong Su
      Pages 107-126
  4. Nonstandard Regularization and Advanced Optimization Theory and Methods

    1. Front Matter

      Pages 139-139
    2. Full Space and Subspace Methods for Large Scale Image Restoration

      • Yanfei Wang, Shiqian Ma, Qinghua Ma
      Pages 183-201
  5. Numerical Inversion in Geoscience and Quantitative Remote Sensing

    1. Front Matter

      Pages 203-203
    2. Some Reconstruction Methods for Inverse Scattering Problems

      • Jijun Liu, Haibing Wang
      Pages 205-247
    3. Tikhonov Regularization for Gravitational Lensing Research

      • Boris Artamonov, Ekaterina Koptelova, Elena Shimanovskaya, Anatoly G. Yagola
      Pages 327-347
  6. Back Matter

    Pages 349-350

About this book

"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.

Editors and Affiliations

  • Key Laboratory of Petroleum Geophysics Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China

    Yanfei Wang, Changchun Yang

  • Department of Mathematics Faculty of Physics, Lomonosov Moscow State University, Moscow, Russia

    Anatoly G. Yagola

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access