000 04061nam a22005775i 4500
001 vtls000560281
003 RU-ToGU
005 20210922090053.0
007 cr nn 008mamaa
008 170212s2015 gw | s |||| 0|eng d
020 _a9783319203256
_9978-3-319-20325-6
024 7 _a10.1007/978-3-319-20325-6
_2doi
035 _ato000560281
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA313
072 7 _aPBWR
_2bicssc
072 7 _aMAT034000
_2bisacsh
082 0 4 _a515.39
_223
082 0 4 _a515.48
_223
100 1 _aLaw, Kody.
_eauthor.
_9466688
245 1 0 _aData Assimilation
_helectronic resource
_bA Mathematical Introduction /
_cby Kody Law, Andrew Stuart, Konstantinos Zygalakis.
250 _a1st ed. 2015.
260 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXVIII, 242 p. 61 illus., 41 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aTexts in Applied Mathematics,
_x0939-2475 ;
_v62
505 0 _aMathematical background -- Discrete Time: Formulation -- Discrete Time: Smoothing Algorithms -- Discrete Time: Filtering Algorithms -- Discrete Time: MATLAB Programs -- Continuous Time: Formulation -- Continuous Time: Smoothing Algorithms -- Continuous Time: Filtering Algorithms -- Continuous Time: MATLAB Programs -- Index. .
520 _aThis book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. The book is organized into nine chapters: the first contains a brief introduction to the mathematical tools around which the material is organized; the next four are concerned with discrete time dynamical systems and discrete time data; the last four are concerned with continuous time dynamical systems and continuous time data and are organized analogously to the corresponding discrete time chapters. This book is aimed at mathematical researchers interested in a systematic development of this interdisciplinary field, and at researchers from the geosciences, and a variety of other scientific fields, who use tools from data assimilation to combine data with time-dependent models. The numerous examples and illustrations make understanding of the theoretical underpinnings of data assimilation accessible. Furthermore, the examples, exercises and MATLAB software, make the book suitable for students in applied mathema tics, either through a lecture course, or through self-study. .
650 0 _amathematics.
_9566183
650 0 _aDynamics.
_9460472
650 0 _aErgodic theory.
_9461180
650 0 _aComputer mathematics.
_9460896
650 0 _aProbabilities.
_9295556
650 0 _aStatistics.
_9124796
650 1 4 _aMathematics.
_9566184
650 2 4 _aDynamical Systems and Ergodic Theory.
_9303500
650 2 4 _aProbability Theory and Stochastic Processes.
_9303734
650 2 4 _aComputational Mathematics and Numerical Analysis.
_9303505
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
_9410653
700 1 _aStuart, Andrew.
_eauthor.
_9466689
700 1 _aZygalakis, Konstantinos.
_eauthor.
_9466690
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aTexts in Applied Mathematics,
_9298055
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-20325-6
912 _aZDB-2-SMA
999 _c414702