Link Download ebook Free: https://ouo.io/OIj9vQ Inverse Problems: Tikhonov Theory And Algorithms Tikhonov Theory and Algorithms By: Kazufumi Ito; Bangti Jin Publisher: WSPC Print ISBN: 9789814596190, 9814596191 eText ISBN: 9789814596213, 9814596213 Pages: 332 Format: EPUB Available from $ 54.00 USD SKU 9789814596213 Inverse problems arise in practical applications whenever one needs to deduce unknowns from observables. This monograph is a valuable contribution to the highly topical field of computational inverse problems. Both mathematical theory and numerical algorithms for model-based inverse problems are discussed in detail. The mathematical theory focuses on nonsmooth Tikhonov regularization for linear and nonlinear inverse problems. The computational methods include nonsmooth optimization algorithms, direct inversion methods and uncertainty quantification via Bayesian inference. The book offers a comprehensive treatment of modern techniques, and seamlessly blends regularization theory with computational methods, which is essential for developing accurate and efficient inversion algorithms for many practical inverse problems. It demonstrates many current developments in the field of computational inversion, such as value function calculus, augmented Tikhonov regularization, multi-parameter Tikhonov regularization, semismooth Newton method, direct sampling method, uncertainty quantification and approximate Bayesian inference. It is written for graduate students and researchers in mathematics, natural science and engineering. Contents: Introduction Models in Inverse Problems Tikhonov Theory for Linear Problems Tikhonov Theory for Nonlinear Inverse Problems Nonsmooth Optimization Direct Inversion Methods Bayesian Inference Readership: Advanced undergraduates, graduates and researchers in applied mathematics, computational mathematics, optimization, statistics, natural science and engineering. It will appeal to those interested in inverse problems.
