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Stochastic Analysis, Filtering, and Stochastic Optimization: A Commemorative Volume to Honor Mark H. A. Davis`s Contributions, Yin George, Zariphopoulou Thaleia


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Автор: Yin George, Zariphopoulou Thaleia
Название:  Stochastic Analysis, Filtering, and Stochastic Optimization: A Commemorative Volume to Honor Mark H. A. Davis`s Contributions
ISBN: 9783030985189
Издательство: Springer
Классификация:


ISBN-10: 3030985180
Обложка/Формат: Hardcover
Страницы: 496
Вес: 0.87 кг.
Дата издания: 24.05.2022
Язык: English
Издание: 1st ed. 2022
Иллюстрации: 40 tables, color; 34 illustrations, color; 16 illustrations, black and white; xxvii, 466 p. 50 illus., 34 illus. in color.
Размер: 23.39 x 15.60 x 2.69 cm
Читательская аудитория: Professional & vocational
Подзаголовок: A commemorative volume to honor mark h. a. davis`s contributions
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This volume is a collection of research works to honor the late Professor Mark H.A. Davis, whose pioneering work in the areas of Stochastic Processes, Filtering, and Stochastic Optimization spans more than five decades. Invited authors include his dissertation advisor, past collaborators, colleagues, mentees, and graduate students of Professor Davis, as well as scholars who have worked in the above areas. Their contributions may expand upon topics in piecewise deterministic processes, pathwise stochastic calculus, martingale methods in stochastic optimization, filtering, mean-field games, time-inconsistency, as well as impulse, singular, risk-sensitive and robust stochastic control.
Дополнительное описание: Control in Hilbert Space and First-Order Mean Field Type Problem (A. Bensoussan).- Risk-Sensitive Markov Decision Problems under Model Uncertainty: Finite Time Horizon Case (R. Bielecki).- Optimal Control of Piecewise Deterministic Markov Processes (F. Du



Stochastic Differential Systems

Автор: M. Metivier; E. Pardoux
Название: Stochastic Differential Systems
ISBN: 3540151761 ISBN-13(EAN): 9783540151760
Издательство: Springer
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Цена: 12157.00 р.
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Stochastic Differential Systems

Автор: B. Grigelionis
Название: Stochastic Differential Systems
ISBN: 3540104984 ISBN-13(EAN): 9783540104988
Издательство: Springer
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Цена: 12157.00 р.
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Filtering and Control of Stochastic Jump Hybrid Systems

Автор: Yao Xiuming, Wu Ligang, Zheng Wei Xing
Название: Filtering and Control of Stochastic Jump Hybrid Systems
ISBN: 3319811525 ISBN-13(EAN): 9783319811529
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Specifically, the considered stochastic jump hybrid systems include Markovian jump Ito stochastic systems, Markovian jump linear-parameter-varying (LPV) systems, Markovian jump singular systems, Markovian jump two-dimensional (2-D) systems, and Markovian jump repeated scalar nonlinear systems.

Stochastic Analysis, Filtering, and Stochastic Optimization

Автор: Yin
Название: Stochastic Analysis, Filtering, and Stochastic Optimization
ISBN: 3030985210 ISBN-13(EAN): 9783030985219
Издательство: Springer
Рейтинг:
Цена: 18167.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This volume is a collection of research works to honor the late Professor Mark H.A. Davis, whose pioneering work in the areas of Stochastic Processes, Filtering, and Stochastic Optimization spans more than five decades. Invited authors include his dissertation advisor, past collaborators, colleagues, mentees, and graduate students of Professor Davis, as well as scholars who have worked in the above areas. Their contributions may expand upon topics in piecewise deterministic processes, pathwise stochastic calculus, martingale methods in stochastic optimization, filtering, mean-field games, time-inconsistency, as well as impulse, singular, risk-sensitive and robust stochastic control.

Stochastic Evolution Systems

Автор: Rozovsky
Название: Stochastic Evolution Systems
ISBN: 331994892X ISBN-13(EAN): 9783319948928
Издательство: Springer
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Цена: 11878.00 р.
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Описание: Covering the general theory of linear stochastic evolution systems with unbounded drift and diffusion operators, this book sureys Ito`s second-order parabolic equations and explores filtering problems for processes whose trajectories can be described by them.

Stochastic Evolution Systems

Автор: B.L. Rozovskii
Название: Stochastic Evolution Systems
ISBN: 0792300378 ISBN-13(EAN): 9780792300373
Издательство: Springer
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Цена: 15372.00 р.
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Описание: 'Et moi, "'J si j'avait su comment en revcnir, One seMcc mathematics has rendered the je n'y semis point aile.' human race. It has put common sense back Jules Verne where it belongs, on the topmost shclf next to the dusty canister labelled 'discarded non- sense'. The series is divergent; therefore we may be able to do something with it. Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non- linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com- puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.

Variance-Constrained Multi-Objective Stochastic Control and Filtering

Автор: Ma
Название: Variance-Constrained Multi-Objective Stochastic Control and Filtering
ISBN: 1118929497 ISBN-13(EAN): 9781118929490
Издательство: Wiley
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Цена: 16782.00 р.
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Stochastic Systems: The Mathematics of Filtering and Identification and Applications

Автор: Michiel Hazewinkel; J.C. Williams
Название: Stochastic Systems: The Mathematics of Filtering and Identification and Applications
ISBN: 9027713308 ISBN-13(EAN): 9789027713308
Издательство: Springer
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Цена: 44861.00 р.
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Fundamentals of Stochastic Filtering

Автор: Alan Bain; Dan Crisan
Название: Fundamentals of Stochastic Filtering
ISBN: 1441926429 ISBN-13(EAN): 9781441926425
Издательство: Springer
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Цена: 13275.00 р.
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Описание: This book provides a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. While no prior knowledge of stochastic filtering is required, readers are assumed to be familiar with measure theory, probability theory and the basics of stochastic processes.

Nonlinear Stochastic Systems with Network-Induced Phenomena

Автор: Jun Hu; Zidong Wang; Huijun Gao
Название: Nonlinear Stochastic Systems with Network-Induced Phenomena
ISBN: 3319359290 ISBN-13(EAN): 9783319359298
Издательство: Springer
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Цена: 14365.00 р.
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Описание: Introduction.- Recursive Filtering for Time-Varying Nonlinear Systems with Stochastic Nonlinearities, Multiple Missing Measurements and Quantized Effects.- Recursive Filtering with Random Parameter Matrices, Multiple Fading Measurements, Probabilistic Sensor Delays, Correlated Noises and Gain-Constraint.- Probability-Guaranteed H-infinity Finite-Horizon Filtering for a Class of Nonlinear Time-Varying Systems with Sensor Saturations.- H-infinity Sliding-Mode Observer Design for a Class of Nonlinear Time-Delay Systems.- Robust Sliding-Mode Control for Uncertain Stochastic Systems with Time-Varying Delays, Randomly-Occurring Nonlinearities and Stochastic Nonlinearities.- Robust Sliding-Mode Control for Stochastic Systems with Randomly-Occurring Uncertainties, Randomly Occurring Nonlinearities, Mixed Time Delays and Markovian Jumping Parameters.- Conclusions and Future Work.

Stochastic Modelling and Filtering

Автор: Alfredo Germani
Название: Stochastic Modelling and Filtering
ISBN: 354017575X ISBN-13(EAN): 9783540175759
Издательство: Springer
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Цена: 16979.00 р.
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Stochastic Filtering With Applications In Finance

Автор: Bhar Ramaprasad
Название: Stochastic Filtering With Applications In Finance
ISBN: 9814304859 ISBN-13(EAN): 9789814304856
Издательство: World Scientific Publishing
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Цена: 18216.00 р.
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Описание: Suitable for graduate level courses on stochastic modeling, this title does not intend to give a complete mathematical treatment of different stochastic filtering approaches, but rather to describe them in simple terms and illustrate their application with real historical data for problems normally encountered in these disciplines.


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