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007			cr||||||||||||
008			100301s2008 xxu| s |||| 0|eng d
020			_a9780387738291
024	7		_a10.1007/978-0-387-73829-1 _2doi
035			_a978-0-387-73829-1
072		7	_aPBKJ _2bicssc
072		7	_aMAT007000 _2bisacsh
082	0	4	_a515.353
090			_amg
100	1		_aPavliotis, Grigorios A. _99017
245	1	0	_aMultiscale Methods _h[electronic resource]: _bAveraging and Homogenization/ _cby Grigorios A. Pavliotis, Andrew M. Stuart.
260			_aNew York: _bSpringer New York, _c2008.
300			_aXVIII, 310 p. _bdigital.
490	0		_aTexts Applied in Mathematics, _x0939-2475; _v53
505	0		_aIntroduction -- Analysis -- Probability Theory and Stochastic Processes -- Ordinary Differential Equations -- Markov Chains -- Stochastic Differential Equations -- Partial Differential Equations -- Invariant Manifolds for ODEs -- Averaging for Markov Chains -- Averaging for ODEs and SDEs -- Homogenization for ODEs and SDEs -- Homogenization for Elliptic PDEs -- Homogenization for Parabolic PDEs -- Averaging for Linear Transport and Parabolic PDEs -- Invariant Manifolds for ODEs: The Convergence Theorem -- Averaging for Markov Chains: The Convergence Theorem -- Averaging for SDEs: The Convergence Theorem -- Homogenization for SDEs: The Convergence Theorem -- Homogenization for Elliptic PDEs: The Convergence Theorem -- Homogenization for Parabolic PDEs: The Convergence Theorem -- Averaging for Linear Transport and Parabolic PDEs: The Convergence Theorem .
520			_aThis introduction to multiscale methods gives readers a broad overview of the many uses and applications of the methods. The book begins by setting the theoretical foundations of the subject area, and moves on to develop a unified approach to the simplification of a wide range of problems which possess multiple scales, via perturbation expansions; differential equations and stochastic processes are studied in one unified framework. The book concludes with an overview of a range of theoretical tools used to justify the simplified models derived via the perturbation expansions. The presentation of the material is particularly suited to the range of mathematicians, scientists and engineers who want to exploit multiscale methods in applications. Extensive use of examples shows how to apply multiscale methods to solving a variety of problems. Exercises then enable readers to build their own skills and put them into practice. Extensions and generalizations of the results presented in the book, as well as references to the literature, are provided in the Discussion and Bibliography section at the end of each chapter. All of the twenty-one chapters are supplemented with exercises. Grigorios Pavliotis is a Lecturer of Mathematics at Imperial College London. Andrew Stuart is a Professor of Mathematics at Warwick University.     &nbsp ;
650		0	_aMathematics _943458
650		0	_aDifferential equations, Partial. _943542
650		0	_aComputer science. _931745
650		0	_aDistribution (Probability theory) _937119
650		0	_aMathematical physics _943632
650		0	_aEngineering mathematics. _937752
697			_aMatemáticas Gerais- _x(inclusive alguns textos elementares sobre assuntos específicos) _923752
700	0		_aStuart, Andrew M _99261
710	1		_aSpringerLink (Online service). _98857
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387738284
830		0	_aTexts in applied mathematics _v53 _98198
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-73829-1
942			_2impa _cEBK
999			_aPAVLIOTIS, Grigorios A.; STUART, Andrew M. <b> Multiscale Methods: </b> Averaging and Homogenization. New York: Springer New York, 2008. XVIII, 310 p (Texts Applied in Mathematics, 0939-2475 ; 53). ISBN 9780387738291. Disponível em: <http://dx.doi.org/10.1007/978-0-387-73829-1 > _c38484 _d38484