Computational Uncertainty Quantification for Inverse Problems

Computational Uncertainty Quantification for Inverse Problems - Computational Science and Engineering

Paperback (30 Sep 2018)

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Publisher's Synopsis

This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanced material on Bayesian methods and UQ, including Markov chain Monte Carlo sampling methods for UQ in inverse problems. Each chapter contains MATLAB® code that implements the algorithms and generates the figures, as well as a large number of exercises accessible to both graduate students and researchers.

Computational Uncertainty Quantification for Inverse Problems is intended for graduate students, researchers, and applied scientists. It is appropriate for courses on computational inverse problems, Bayesian methods for inverse problems, and UQ methods for inverse problems.

Book information

ISBN: 9781611975376
Publisher: SIAM - Society for Industrial and Applied Mathematics
Imprint: Society for Industrial and Applied Mathematics
Pub date:
DEWEY: 515.353
DEWEY edition: 23
Language: English
Number of pages: viii, 133
Weight: 322g
Height: 179mm
Width: 258mm
Spine width: 17mm