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Published by World Scientific Publishing Comp, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer 2012-01, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by Springer Berlin Heidelberg Jan 2012, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Gaussian processes can be viewed as a far-reaching infinite-dimensional extension of classical normal random variables. Their theory presents a powerful range of tools for probabilistic modelling in various academic and technical domains such as Statistics, Forecasting, Finance, Information Transmission, Machine Learning - to mention just a few. The objective of these Briefs is to present a quick and condensed treatment of the core theory that a reader must understand in order to make his own independent contributions. The primary intended readership are PhD/Masters students and researchers working in pure or applied mathematics. The first chapters introduce essentials of the classical theory of Gaussian processes and measures with the core notions of reproducing kernel, integral representation, isoperimetric property, large deviation principle. The brevity being a priority for teaching and learning purposes, certain technical details and proofs are omitted. The later chapters touch important recent issues not sufficiently reflected in the literature, such as small deviations, expansions, and quantization of processes. In university teaching, one can build a one-semester advanced course upon these Briefs. 132 pp. Englisch.
Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by Springer Verlag, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by World Scientific, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
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Published by Springer Berlin Heidelberg, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Gaussian processes can be viewed as a far-reaching infinite-dimensional extension of classical normal random variables. Their theory presents a powerful range of tools for probabilistic modelling in various academic and technical domains such as Statistics, Forecasting, Finance, Information Transmission, Machine Learning - to mention just a few. The objective of these Briefs is to present a quick and condensed treatment of the core theory that a reader must understand in order to make his own independent contributions. The primary intended readership are PhD/Masters students and researchers working in pure or applied mathematics. The first chapters introduce essentials of the classical theory of Gaussian processes and measures with the core notions of reproducing kernel, integral representation, isoperimetric property, large deviation principle. The brevity being a priority for teaching and learning purposes, certain technical details and proofs are omitted. The later chapters touch important recent issues not sufficiently reflected in the literature, such as small deviations, expansions, and quantization of processes. In university teaching, one can build a one-semester advanced course upon these Briefs.
Published by Springer Berlin Heidelberg, 2012
ISBN 10: 3642249388ISBN 13: 9783642249389
Seller: moluna, Greven, Germany
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Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
Seller: moluna, Greven, Germany
Book Print on Demand
Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. InhaltsverzeichnisBrief Reminder of Probability Theory Compound Poisson, Infinitely Divisible and Stable Random Variables Gaussian Processes: Wiener Process, Fractional Brownian Motion, Etc. Levy Processes Uncorrelated and Independen.
Published by World Scientific Publishing Company, 2014
ISBN 10: 9814522287ISBN 13: 9789814522281
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book Print on Demand
Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This volume first introduces the mathematical tools necessary for understanding and working with a broad class of applied stochastic models. The toolbox includes Gaussian processes, independently scattered measures such as Gaussian white noise and Poisson random measures, stochastic integrals, compound Poisson, infinitely divisible and stable distributions and processes.