Stochastic partial differential equations, Lototsky, Sergey V. Rozovsky, Boris L.

Автор: Shreve
Название: Stochastic Calculus for Finance I
ISBN: 0387401008 ISBN-13(EAN): 9780387401003
Издательство: Springer
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Цена: 8384.00 р.
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Описание: Developed for the professional Master`s program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S. Has been tested in the classroom and revised over a period of several yearsExercises conclude every chapter;

Автор: Xie
Название: Differential Equations for Engineers
ISBN: 1107632951 ISBN-13(EAN): 9781107632950
Издательство: Cambridge Academ
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Цена: 9504.00 р.
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Описание: Xie presents a systematic introduction to differential equations for engineering students. The relevance of differential equations in engineering applications motivates readers, and studies of various types of differential equations are determined by engineering applications. The theory and techniques for solving differential equations are then applied to solve practical engineering problems.

Автор: Guillermo Sapiro
Название: Geometric Partial Differential Equations and Image Analysis
ISBN: 0521685079 ISBN-13(EAN): 9780521685078
Издательство: Cambridge Academ
Цена: 8078.00 р.
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Описание: Researchers and practitioners will be able to achieve state-of-the-art practical results in a large number of real problems with the techniques described here. Applications covered include image segmentation, shape analysis, image enhancement, and tracking.

Автор: Peter Kotelenez
Название: Stochastic Ordinary and Stochastic Partial Differential Equations
ISBN: 1489986588 ISBN-13(EAN): 9781489986580
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book analyzes mathematical models of time-dependent physical phenomena on microscopic, macroscopic and mesoscopic levels. It provides a rigorous derivation of each level from the preceding one and examines the resulting mesoscopic equations in detail.

Название: Stochastic Differential Equations, Backward SDEs, Partial Di
ISBN: 3319057138 ISBN-13(EAN): 9783319057132
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This research monograph presents results to researchers in stochastic calculus, forward and backward stochastic differential equations, connections between diffusion processes and second order partial differential equations (PDEs), and financial mathematics.

Автор: Zhongqiang Zhang; George Em Karniadakis
Название: Numerical Methods for Stochastic Partial Differential Equations with White Noise
ISBN: 3319575104 ISBN-13(EAN): 9783319575100
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book covers numerical methods for stochastic partial differential equations with white noise using the framework of Wong-Zakai approximation. In addition, stochastic Euler equations are exploited as an application of stochastic collocation methods, where a numerical comparison with other integration methods in random space is made.

Автор: Y. Rozanov
Название: Random Fields and Stochastic Partial Differential Equations
ISBN: 0792349849 ISBN-13(EAN): 9780792349846
Издательство: Springer
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Цена: 13275.00 р.
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Описание: This book considers some models described by means of partial differential equations and boundary conditions with chaotic stochastic disturbance. In a framework of stochastic partial differential equations an approach is suggested to generalize solutions of stochastic boundary problems.

Автор: Giuseppe Da Prato; Luciano Tubaro
Название: Stochastic Partial Differential Equations and Applications
ISBN: 3540172114 ISBN-13(EAN): 9783540172116
Издательство: Springer
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Цена: 6288.00 р.
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Автор: Weintraub, Steven
Название: Differential forms
ISBN: 0123944031 ISBN-13(EAN): 9780123944030
Издательство: Elsevier Science
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Цена: 14820.00 р.
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Описание: Offers many examples of computations and research applications across the fields of applied mathematics, engineering, and physics. This title provides a solid theoretical basis of how to develop and apply differential forms to real research problems. It includes computational methods for graphical results essential for math modeling.