Inverse Problems: Tikhonov Theory And Algorithms (Hardcover)

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.

General

Imprint:	World Scientific Publishing Co Pte Ltd
Country of origin:	Singapore
Series:	Series On Applied Mathematics, 22
Release date:	October 2014
First published:	2015
Authors:	Kazufumi Ito • Bangti Jin
Dimensions:	237 x 163 x 22mm (L x W x T)
Format:	Hardcover - Cloth over boards
Pages:	332
ISBN-13:	978-981-4596-19-0
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	981-4596-19-1
Barcode:	9789814596190

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