000			03891nam a22004455i 4500
999			_c387525 _d387525
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003			ES-MaUEC
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007			cr nn 008mamaa
008			220601s2018 sz | s |||| 0|eng d
020			_a9783031024115
024	7		_a10.1007/978-3-031-02411-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA372 _b2018
100	1		_aSalehi, Younes _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aNumerical Integration of Space Fractional Partial Differential Equations _bVol 1 - Introduction to Algorithms and Computer Coding in R _cby Younes Salehi, William E. Schiesser.
250			_a1st edition 2018
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (XII, 188 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Mathematics & Statistics _x1938-1751
505	0		_aPreface -- Introduction to Fractional Partial Differential Equations -- Variation in the Order of the Fractional Derivatives -- Dirichlet, Neumann, Robin BCs -- Convection SFPDEs -- Nonlinear SFPDEs -- Authors' Biographies -- Index.
520			_aPartial differential equations (PDEs) are one of the most used widely forms of mathematics in science and engineering. PDEs can have partial derivatives with respect to (1) an initial value variable, typically time, and (2) boundary value variables, typically spatial variables. Therefore, two fractional PDEs can be considered, (1) fractional in time (TFPDEs), and (2) fractional in space (SFPDEs). The two volumes are directed to the development and use of SFPDEs, with the discussion divided as: Vol 1: Introduction to Algorithms and Computer Coding in R Vol 2: Applications from Classical Integer PDEs. Various definitions of space fractional derivatives have been proposed. We focus on the Caputo derivative, with occasional reference to the Riemann-Liouville derivative. The Caputo derivative is defined as a convolution integral. Thus, rather than being local (with a value at a particular point in space), the Caputo derivative is non-local (it is based on an integration in space), which is one of the reasons that it has properties not shared by integer derivatives. A principal objective of the two volumes is to provide the reader with a set of documented R routines that are discussed in detail, and can be downloaded and executed without having to first study the details of the relevant numerical analysis and then code a set of routines. In the first volume, the emphasis is on basic concepts of SFPDEs and the associated numerical algorithms. The presentation is not as formal mathematics, e.g., theorems and proofs. Rather, the presentation is by examples of SFPDEs, including a detailed discussion of the algorithms for computing numerical solutions to SFPDEs and a detailed explanation of the associated source code.
988			_aSynthesis Collection of Technology_2018
650		7	_2embne _9157537 _aAnálisis espacial (Estadística)
650		7	_2embne _9145456 _aEcuaciones en derivadas parciales
650		7	_2embne _9164496 _aR (Lenguaje de programación)
700	1		_aSchiesser, William E. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9670222
776	0	8	_iPrinted edition: _z9783031002571
776	0	8	_iPrinted edition: _z9783031012839
776	0	8	_iPrinted edition: _z9783031035395
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02411-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI