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.
Автор: Lakhdar Aggoun Название: Measure Theory and Filtering ISBN: 0521838037 ISBN-13(EAN): 9780521838030 Издательство: Cambridge Academ Рейтинг: Цена: 6973 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Aggoun Название: Measure Theory and Filtering ISBN: 1107410711 ISBN-13(EAN): 9781107410718 Издательство: Cambridge Academ Рейтинг: 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.
Автор: Elworthy Название: The Geometry of Filtering ISBN: 3034601751 ISBN-13(EAN): 9783034601757 Издательство: Springer Рейтинг: Цена: 4674 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
Автор: Crisan, Dan; Rozovskii, Boris Название: The Oxford Handbook of Nonlinear Filtering ISBN: 0199532907 ISBN-13(EAN): 9780199532902 Издательство: Oxford Academ Рейтинг: 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.
Автор: S?rkk? Название: Bayesian Filtering and Smoothing ISBN: 1107619289 ISBN-13(EAN): 9781107619289 Издательство: Cambridge Academ Рейтинг: Цена: 3121 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.
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.
Автор: Fanbiao Li; Peng Shi; Ligang Wu Название: Control and Filtering for Semi-Markovian Jump Systems ISBN: 3319471988 ISBN-13(EAN): 9783319471983 Издательство: Springer Рейтинг: Цена: 12233 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Babones Salvatore Название: Fundamentals of Regression Modeling ISBN: 1446208281 ISBN-13(EAN): 9781446208281 Издательство: Sage Publications Рейтинг: Цена: 76110 р. Наличие на складе: Поставка под заказ.
Описание: This new four-volume major work presents a collection of landmark studies on the topic of regression modeling, identifying the most important, fundamental articles out of thousands of relevant contributions. The social sciences - particularly sociology and political science - have made extensive use of regression models since the 1960s, and regression modeling continues to be the staple method of the field. The collection is framed by an orienting essay which presents to a guide to regression modelling, written with applied practitioners in mind.
Автор: Laird Название: The fundamentals of modern statistical genetics ISBN: 1441973370 ISBN-13(EAN): 9781441973375 Издательство: Springer Рейтинг: Цена: 7479 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.
Автор: Nguyen Hung T., Wu Berlin Название: Fundamentals of Statistics with Fuzzy Data ISBN: 3540316957 ISBN-13(EAN): 9783540316954 Издательство: Springer Рейтинг: Цена: 14024 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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