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Fundamentals of Kalman Filtering, Zarchan, Paul


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Цена: 8196р.
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Автор: Zarchan, Paul
Название:  Fundamentals of Kalman Filtering   (Основные принципы фильтрования)
Издательство: Eurospan
Классификация:
Вероятность и статистика

ISBN: 1563476940
ISBN-13(EAN): 9781563476945
ISBN: 1-56347-694-0
ISBN-13(EAN): 978-1-56347-694-5
Обложка/Формат: Hardback
Страницы: 746 pages, Illustrat
Вес: 1.21 кг.
Дата издания: 31/03/2005
Серия: Progress in astronautics & aeronautics series
Язык: ENG
Издание: 2 rev ed
Иллюстрации: Illustrations
Размер: 233 x 168 mm, 1202 grams
Читательская аудитория: Professional & VocationalTertiary Education (US: C
Подзаголовок: A practical approach
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Поставляется из: Англии



Spatial Autocorrelation and Spatial Filtering / Gaining Understanding Through Theory and Scientific Visualization

Автор: Griffith Daniel A.
Название: Spatial Autocorrelation and Spatial Filtering / Gaining Understanding Through Theory and Scientific Visualization
ISBN: 3540009329 ISBN-13(EAN): 9783540009320
Издательство: Springer
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Цена: 15728 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Exploiting the old maxim that "a picture is worth a thousand words," scientific visualization may be defined as the transformation of numerical scientific data into informative graphical displays. It introduces a nonverbal model into subdisciplines that hitherto employed mostly or only mathematical or verbal-conceptual models. The focus of this monograph is on how scientific visualization can help revolutionize the manner in which the tendencies for (dis)similar numerical values to cluster together in location on a map are explored and analyzed, affording spatial data analyses that are better understood, presented, and used. In doing so, the concept known as spatial autocorrelation - which characterizes these tendencies and is one of the key features of georeferenced data, or data tagged to the earth's surface - is further de-mystified. This self-correlation arises from relative locations in geographic space.

Schuss, Nonlinear Filtering and Optimal Phase Tracking (Applied Mathematical Sciences 180)

Название: Schuss, Nonlinear Filtering and Optimal Phase Tracking (Applied Mathematical Sciences 180)
ISBN: 146140486X ISBN-13(EAN): 9781461404866
Издательство: Springer
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Цена: 5605 р.
Наличие на складе: Поставка под заказ.

Описание:  This book offers an analytical rather than measure-theoretical approach to the derivation of the partial differential equations of nonlinear filtering theory. The basis for this approach is the discrete numerical scheme used in Monte-Carlo simulations of stochastic differential equations and Wiener's associated path integral representation of the transition probability density. Furthermore, it presents analytical methods for constructing asymptotic approximations to their solution and for synthesizing asymptotically optimal filters. It also offers a new approach to the phase tracking problem, based on optimizing the mean time to loss of lock. The book is based on lecture notes from a one-semester special topics course on stochastic processes and their applications that the author taught many times to graduate students of mathematics, applied mathematics, physics, chemistry, computer science, electrical engineering, and other disciplines. The book contains exercises and worked-out examples aimed at illustrating the methods of mathematical modeling and performance analysis of phase trackers.

Fundamentals of Statistical Reasoning in Education

Автор: Coladarci
Название: Fundamentals of Statistical Reasoning in Education
ISBN: 0470574798 ISBN-13(EAN): 9780470574799
Издательство: Wiley
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Цена: 51571 р.
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Fundamentals of Statistics with Fuzzy Data

Автор: Nguyen Hung T., Wu Berlin
Название: Fundamentals of Statistics with Fuzzy Data
ISBN: 3540316957 ISBN-13(EAN): 9783540316954
Издательство: Springer
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Цена: 14024 р.
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Описание: Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications.

Measure Theory and Filtering

Автор: Lakhdar Aggoun
Название: Measure Theory and Filtering
ISBN: 0521838037 ISBN-13(EAN): 9780521838030
Издательство: Cambridge Academ
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Цена: 6973 р.
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Описание: The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus based probability theory. As conditional expectation is the key concept, the correct setting for filtering theory is that of a probability space. Graduate engineers, mathematicians and those working in quantitative finance wishing to use filtering techniques will find in the first half of this book an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion. Exercises are included. The book then provides an excellent users’ guide to filtering: basic theory is followed by a thorough treatment of Kalman filtering, including recent results which extend the Kalman filter to provide parameter estimates. These ideas are then applied to problems arising in finance, genetics and population modelling in three separate chapters, making this a comprehensive resource for both practitioners and researchers.

The Geometry of Filtering

Автор: Elworthy
Название: The Geometry of Filtering
ISBN: 3034601751 ISBN-13(EAN): 9783034601757
Издательство: Springer
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Цена: 4674 р.
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Описание: The geometry used in this book is that determined by a map of one space N onto another, M, mapping a diffusion process, or operator, on N to one on M. That geometry is considered in situations of geometric, stochastic analytic or filtering interest.

Bayesian Filtering and Smoothing

Автор: S?rkk?
Название: Bayesian Filtering and Smoothing
ISBN: 1107619289 ISBN-13(EAN): 9781107619289
Издательство: Cambridge Academ
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Цена: 3121 р.
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Описание: Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. Readers learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how state-of-the-art Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book's practical and algorithmic approach assumes only modest mathematical prerequisites. Examples include Matlab computations, and the numerous end-of-chapter exercises include computational assignments. Matlab code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.

Bayesian Filtering and Smoothing

Автор: S?rkk?
Название: Bayesian Filtering and Smoothing
ISBN: 110703065X ISBN-13(EAN): 9781107030657
Издательство: Cambridge Academ
Рейтинг:
Цена: 8326 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. Readers learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how state-of-the-art Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book's practical and algorithmic approach assumes only modest mathematical prerequisites. Examples include Matlab computations, and the numerous end-of-chapter exercises include computational assignments. Matlab code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.

Measure Theory and Filtering

Автор: Aggoun
Название: Measure Theory and Filtering
ISBN: 1107410711 ISBN-13(EAN): 9781107410718
Издательство: Cambridge Academ
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Цена: 4162 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book was published in 2004. The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus-based probability theory. As conditional expectation is the key concept, the correct setting for filtering theory is that of a probability space. Graduate engineers, mathematicians and those working in quantitative finance wishing to use filtering techniques will find in the first half of this book an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion. Exercises are included. The book then provides an excellent users' guide to filtering: basic theory is followed by a thorough treatment of Kalman filtering, including recent results which extend the Kalman filter to provide parameter estimates. These ideas are then applied to problems arising in finance, genetics and population modelling in three separate chapters, making this a comprehensive resource for both practitioners and researchers.

The Oxford Handbook of Nonlinear Filtering

Автор: Crisan, Dan; Rozovskii, Boris
Название: The Oxford Handbook of Nonlinear Filtering
ISBN: 0199532907 ISBN-13(EAN): 9780199532902
Издательство: Oxford Academ
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Цена: 12490 р.
Наличие на складе: Поставка под заказ.

Описание: A comprehensive, interdisciplinary resource for nonlinear (or stochastic) filtering, this Handbook explores the classical theory, the recent advances, and the application of nonlinear filtering to mathematical finance. With contributions from 58 leading experts, it will prove invaluable to anyone working in, or wishing to know more about, the area.

Control and Filtering for Semi-Markovian Jump Systems

Автор: Fanbiao Li; Peng Shi; Ligang Wu
Название: Control and Filtering for Semi-Markovian Jump Systems
ISBN: 3319471988 ISBN-13(EAN): 9783319471983
Издательство: Springer
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Цена: 12233 р.
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Описание: This book presents up-to-date research developments and novel methodologies on semi-Markovian jump systems (S-MJS). It presents solutions to a series of problems with new approaches for the control and filtering of S-MJS, including stability analysis, sliding mode control, dynamic output feedback control, robust filter design, and fault detection. A set of newly developed techniques such as piecewise analysis method, positively invariant set approach, event-triggered method, and cone complementary linearization approaches are presented. Control and Filtering for Semi-Markovian Jump Systems is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

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: 11900 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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