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Stochastic PDEs and Dynamics, Boling Guo, Hongjun Gao, Xueke Pu


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Цена: 18586.00р.
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Автор: Boling Guo, Hongjun Gao, Xueke Pu
Название:  Stochastic PDEs and Dynamics
ISBN: 9783110495102
Издательство: Walter de Gruyter
Классификация:





ISBN-10: 3110495104
Обложка/Формат: Hardback
Страницы: 228
Вес: 0.57 кг.
Дата издания: 21.11.2016
Серия: Mathematics
Язык: English
Размер: 244 x 170 x 14
Читательская аудитория: Professional and scholarly
Ключевые слова: Differential calculus & equations,Probability & statistics,Stochastics,Nonlinear science, MATHEMATICS / Differential Equations / Partial,MATHEMATICS / Mathematical Analysis,MATHEMATICS / Probability & Statistics / General,MATHEMATICS / Probability & Stati
Основная тема: MATHEMATICS / Probability & Statistics / Stochastic,SCIENCE / Physics / Mathematical & Computational,MATHEMATICS / Mathematical Analysis,MATHEMATICS / Differential Equations / Partial
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book explains mathematical theories of a collection of stochastic partial differential equations and their dynamical behaviors. Based on probability and stochastic process, the authors discuss stochastic integrals, Ito formula and Ornstein-Uhlenbeck processes, and introduce theoretical framework for random attractors. With rigorous mathematical deduction, the book is an essential reference to mathematicians and physicists in nonlinear science. Contents: PreliminariesThe stochastic integral and It formulaOU processes and SDEsRandom attractorsApplicationsBibliographyIndex


Stochastic Processes

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Цена: 11246.00 р.
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Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.

Free Boundary Problems in PDEs and Particle Systems

Автор: Carinci
Название: Free Boundary Problems in PDEs and Particle Systems
ISBN: 3319333690 ISBN-13(EAN): 9783319333694
Издательство: Springer
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Цена: 6986.00 р.
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Описание:

In this volume a theory for models of transport in the presence of a free boundary is developed.
Macroscopic laws of transport are described by PDE's.
When the system is open, there are several mechanisms to couple the system with the external forces. Here a class of systems where the interaction with the exterior takes place in correspondence of a free boundary is considered. Both continuous and discrete models sharing the same structure are analysed.
In Part I a free boundary problem related to the Stefan Problem is worked out in all details. For this model a new notion of relaxed solution is proposed for which global existence and uniqueness is proven. It is also shown that this is the hydrodynamic limit of the empirical mass density of the associated particle system. In Part II several other models are discussed. The expectation is that the results proved for the basic model extend to these other cases.
All the models discussed in this volume have an interest in problems arising in several research fields such as heat conduction, queuing theory, propagation of fire, interface dynamics, population dynamics, evolution of biological systems with selection mechanisms.
In general researchers interested in the relations between PDE’s and stochastic processes can find in this volume an extension of this correspondence to modern mathematical physics.
An Introduction to Computational Stochastic PDEs

Автор: Lord
Название: An Introduction to Computational Stochastic PDEs
ISBN: 0521899907 ISBN-13(EAN): 9780521899901
Издательство: Cambridge Academ
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Цена: 18216.00 р.
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Описание: This comprehensive introduction to stochastic partial differential equations incorporates the effects of randomness into real-world models, offering graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. MATLAB (R) codes are included, so that readers can perform computations themselves and solve the test problems discussed.

Stochastic processes

Автор: Parzen, Emanuel
Название: Stochastic processes
ISBN: 0898714419 ISBN-13(EAN): 9780898714418
Издательство: Mare Nostrum (Eurospan)
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Цена: 9656.00 р.
Наличие на складе: Нет в наличии.

Описание: This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions.

Geometric Properties for Parabolic and Elliptic PDE`s

Автор: Gazzola
Название: Geometric Properties for Parabolic and Elliptic PDE`s
ISBN: 3319415360 ISBN-13(EAN): 9783319415369
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book collects recent research papers by respected specialists in the field. It presents advances in the field of geometric properties for parabolic and elliptic partial differential equations, an area that has always attracted great attention. It settles the basic issues (existence, uniqueness, stability and regularity of solutions of initial/boundary value problems) before focusing on the topological and/or geometric aspects. These topics interact with many other areas of research and rely on a wide range of mathematical tools and techniques, both analytic and geometric. The Italian and Japanese mathematical schools have a long history of research on PDEs and have numerous active groups collaborating in the study of the geometric properties of their solutions.

An Introduction to Computational Stochastic PDEs

Автор: Lord
Название: An Introduction to Computational Stochastic PDEs
ISBN: 0521728525 ISBN-13(EAN): 9780521728522
Издательство: Cambridge Academ
Рейтинг:
Цена: 9029.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This comprehensive introduction to stochastic partial differential equations incorporates the effects of randomness into real-world models, offering graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. MATLAB (R) codes are included, so that readers can perform computations themselves and solve the test problems discussed.


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