000			01703 a2200229 4500
999			_c5763 _d5763
005			20250901171857.0
008			250827b ||||| |||| 00| 0 eng d
020			_a9780387220734
041			_aeng
082			_a515.357 KAI/S
100			_aKaipio, Jari _914437
245			_aStatistical and computational inverse problems
260			_bSpringer _aNew York _cc2005
300			_axvi, 339p.; 23cm.
520			_aThis 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.
650			_aMathematics analysis  _914438
650			_aDifferential calculus _9929
650			_aDifferental equations _97899
700			_aSomersalo, Erkki _914434
856			_uhttps://doi.org/10.1007/b138659
942			_cBK