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Recurrence Quantification Analysis, Charles L. Webber, Jr.; Norbert Marwan


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Цена: 13275.00р.
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При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Charles L. Webber, Jr.; Norbert Marwan
Название:  Recurrence Quantification Analysis
ISBN: 9783319071541
Издательство: Springer
Классификация:
ISBN-10: 3319071548
Обложка/Формат: Hardcover
Страницы: 421
Вес: 0.79 кг.
Дата издания: 12.08.2014
Серия: Understanding Complex Systems
Язык: English
Издание: 2015 ed.
Иллюстрации: 103 black & white illustrations, 107 colour illustrations, biography
Размер: 243 x 162 x 28
Читательская аудитория: Professional & vocational
Основная тема: Applications of Nonlinear Dynamics and Chaos Theory
Подзаголовок: Theory and Best Practices
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: The analysis of recurrences in dynamical systems by using recurrence plots and their quantification is still an emerging field.


Recurrence in Ergodic Theory and Combinatorial Number Theory

Автор: Furstenberg Harry
Название: Recurrence in Ergodic Theory and Combinatorial Number Theory
ISBN: 0691615365 ISBN-13(EAN): 9780691615363
Издательство: Wiley
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Цена: 6336.00 р.
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Описание: Topological dynamics and ergodic theory usually have been treated independently. H. Furstenberg, instead, develops the common ground between them by applying the modern theory of dynamical systems to combinatories and number theory. Originally published in 1981. The Princeton Legacy Library uses the latest print-on-demand technology to again make

Spectral Methods for Uncertainty Quantification

Автор: Olivier Le Maitre; Omar M Knio
Название: Spectral Methods for Uncertainty Quantification
ISBN: 9400731922 ISBN-13(EAN): 9789400731929
Издательство: Springer
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Цена: 11878.00 р.
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Описание: This book presents applications of spectral methods to problems of uncertainty propagation and quantification in model-based computations, focusing on the computational and algorithmic features of these methods most useful in dealing with models based on partial differential equations, in particular models arising in simulations of fluid flows.

Uncertainty Quantification in Computational Fluid Dynamics

Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri
Название: Uncertainty Quantification in Computational Fluid Dynamics
ISBN: 3319346660 ISBN-13(EAN): 9783319346663
Издательство: Springer
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Цена: 15372.00 р.
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Описание: It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space.

Uncertainty Quantification for Hyperbolic and Kinetic Equations

Автор: Shi Jin; Lorenzo Pareschi
Название: Uncertainty Quantification for Hyperbolic and Kinetic Equations
ISBN: 331967109X ISBN-13(EAN): 9783319671093
Издательство: Springer
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Цена: 13275.00 р.
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Описание: This book explores recent advances in uncertainty quantification for hyperbolic, kinetic, and related problems. The contributions address a range of different aspects, including: polynomial chaos expansions, perturbation methods, multi-level Monte Carlo methods, importance sampling, and moment methods.

Large-Scale Inverse Problems and Quantification of Uncertainty

Автор: Biegler
Название: Large-Scale Inverse Problems and Quantification of Uncertainty
ISBN: 0470697431 ISBN-13(EAN): 9780470697436
Издательство: Wiley
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Цена: 17733.00 р.
Наличие на складе: Поставка под заказ.

Описание: This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems.

Introduction to Uncertainty Quantification

Автор: Sullivan, T.J.
Название: Introduction to Uncertainty Quantification
ISBN: 3319233947 ISBN-13(EAN): 9783319233949
Издательство: Springer
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Цена: 8384.00 р.
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Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study. Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field.


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