000			03379nam a2200421 a 4500
001			000q0401
003			WSP
005			20260416153407.0
007			cr |nu|||unuuu
008			221027s2023 enk ob 001 0 eng d
010			_a2022045798
020			_a9781800613584 _q(ebook)
020			_a180061358X _q(ebook)
020			_z9781800613577 _q(hbk.)
040			_aWSPC _beng _cWSPC
050		4	_aQA274.2
072		7	_aMAT _x007000 _2bisacsh
072		7	_aMAT _x003000 _2bisacsh
072		7	_aMAT _x005000 _2bisacsh
082	0	4	_a519.2/2 _223
049			_aMAIN
100	1		_aSaha Ray, Santanu.
245	1	0	_aStochastic integral and differential equations in mathematical modelling / _cSantanu Saha Ray.
260			_aLondon : _bWorld Scientific Publishing Europe Ltd., _cc2023.
300			_a1 online resource (xxviii, 320 p.)
504			_aIncludes bibliographical references and index.
505	0		_aIntroduction and preliminaries of stochastic calculus -- Analytical solutions of stochastic differential equations -- Numerical solutions of stochastic integral equation -- Numerical solutions of multidimensional stochastic integral equation -- Numerical solutions of stochastic integral equations with fractional Brownian motion -- Numerical solutions of stochastic differential equations arising in physical phenomena -- Numerical solutions of stochastic point kinetics equations -- Numerical solutions of fractional stochastic point kinetics equation -- Conclusion and future directions.
520			_a"The modelling of systems by differential equations usually requires that the parameters involved be completely known. Such models often originate from problems in physics or economics where we have insufficient information on parameter values. One important class of stochastic mathematical models is stochastic partial differential equations (SPDEs), which can be seen as deterministic partial differential equations (PDEs) with finite or infinite dimensional stochastic processes - either with colour noise or white noise. Though white noise is a purely mathematical construction, it can be a good model for rapid random fluctuations. Stochastic Integral and Differential Equations in Mathematical Modelling concerns the analysis of discrete-time approximations for stochastic differential equations (SDEs) driven by Wiener processes. It also provides a theoretical basis for working with SDEs and stochastic processes. This book is written in a simple and clear mathematical logical language, with basic definitions and theorems on stochastic calculus provided from the outset. Each chapter contains illustrated examples via figures and tables. The reader can also construct new wavelets by using the procedure presented in the book. Stochastic Integral and Differential Equations in Mathematical Modelling fulfils the existing gap in the literature for a comprehensive account of this subject area"-- _cPublisher's website.
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat Reader.
650		0	_aStochastic models.
650		0	_aStochastic analysis _xMathematical models.
650		0	_aStochastic integral equations.
650		0	_aStochastic differential equations.
655		0	_aElectronic books.
856	4	0	_uhttps://www.worldscientific.com/worldscibooks/10.1142/q0401#t=toc
942			_cE-BOOK
999			_c49726 _d49726