| 书目名称 | Statistical and Computational Inverse Problems | | 编辑 | Jari P. Kaipio,Erkki Somersalo | | 视频video | | | 概述 | Includes supplementary material: | | 丛书名称 | Applied Mathematical Sciences | | 图书封面 |  | | 描述 | This book is aimed at postgraduate students in applied mathematics as well as at engineering and physics students with a ?rm background in mathem- ics. The ?rst four chapters can be used as the material for a ?rst course on inverse problems with a focus on computational and statistical aspects. On the other hand, Chapters 3 and 4, which discuss statistical and nonstati- ary inversion methods, can be used by students already having knowldege of classical inversion methods. There is rich literature, including numerous textbooks, on the classical aspects of inverse problems. From the numerical point of view, these books concentrate on problems in which the measurement errors are either very small or in which the error properties are known exactly. In real-world pr- lems, however, the errors are seldom very small and their properties in the deterministic sensearenot wellknown.For example,inclassicalliteraturethe errornorm is usuallyassumed to be a known realnumber. In reality,the error norm is a random variable whose mean might be known. | | 出版日期 | Book 2005 | | 关键词 | Markov; Measure; Probability distribution; Random variable; biomedical engineering; construction; mechanic | | 版次 | 1 | | doi | https://doi.org/10.1007/b138659 | | isbn_softcover | 978-1-4419-1964-9 | | isbn_ebook | 978-0-387-27132-3Series ISSN 0066-5452 Series E-ISSN 2196-968X | | issn_series | 0066-5452 | | copyright | Springer-Verlag New York 2005 |
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发表于 2025-3-21 17:38:23
