000			03182nam a22005655i 4500
001			978-3-319-22410-7
003			DE-He213
005			20200421111704.0
007			cr nn 008mamaa
008			150916s2016 gw | s |||| 0|eng d
020			_a9783319224107 _9978-3-319-22410-7
024	7		_a10.1007/978-3-319-22410-7 _2doi
050		4	_aQA76.9.C65
072		7	_aUGK _2bicssc
072		7	_aCOM072000 _2bisacsh
082	0	4	_a003.3 _223
100	1		_aGuzzi, Rodolfo. _eauthor.
245	1	0	_aData Assimilation: Mathematical Concepts and Instructive Examples _h[electronic resource] / _cby Rodolfo Guzzi.
250			_a1st ed. 2016.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016.
300			_aVIII, 135 p. 4 illus., 1 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Earth Sciences, _x2191-5369
505	0		_aPreface -- 1. Introduction through historical perspective -- 2. Representation of the physical system -- 3. Sequential interpolation -- 4. Advanced data assimilation methods -- 5. Applications -- A. Appendix.
520			_aThis book endeavours to give a concise contribution to understanding the data assimilation and related methodologies. The mathematical concepts and related algorithms are fully presented, especially for those facing this theme for the first time.  The first chapter gives a wide overview of the data assimilation steps starting from Gauss' first methods to the most recent as those developed under the Monte Carlo methods.  The second chapter treats the representation of the physical  system as an ontological basis of the problem. The third chapter deals with the classical Kalman filter, while the fourth chapter deals with the advanced methods based on  recursive Bayesian Estimation. A special chapter, the fifth, deals with the possible applications, from the first Lorenz model, passing trough the biology and medicine up to planetary assimilation, mainly on Mars. This book serves both teachers and college students, and other interested parties providing the algorithms and formulas to manage the data assimilation everywhere a dynamic system is present.
650		0	_aComputer science.
650		0	_aWater quality.
650		0	_aWater pollution.
650		0	_aPhysical geography.
650		0	_aEnvironmental sciences.
650		0	_aComputer simulation.
650		0	_aPhysics.
650	1	4	_aComputer Science.
650	2	4	_aSimulation and Modeling.
650	2	4	_aEarth System Sciences.
650	2	4	_aTheoretical, Mathematical and Computational Physics.
650	2	4	_aEnvironmental Science and Engineering.
650	2	4	_aWater Quality/Water Pollution.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319224091
830		0	_aSpringerBriefs in Earth Sciences, _x2191-5369
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-22410-7
912			_aZDB-2-SCS
942			_cEBK
999			_c55180 _d55180