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ISBN 10: 9814522287 ISBN 13: 9789814522281
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ISBN 10: 9814522287 ISBN 13: 9789814522281
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Lectures on Gaussian Processes | Mikhail Lifshits | Taschenbuch | SpringerBriefs in Mathematics | x | Englisch | 2012 | Springer | EAN 9783642249389 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Editore: Moscow, 1974
Da: BiblioEra, Everett, MA, U.S.A.
Hardcover. Condizione: Good. In Russian. Lifshits, Mikhail Alexandrovich. Irreplaceable Tradition. Moscow: Art, 1974. All images are for identification of editions only. Several books of the same edition may be available. Please feel free to request photos of available books.SKU7157085.
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Lingua: Inglese
Editore: Springer Berlin Heidelberg Jan 2012, 2012
ISBN 10: 3642249388 ISBN 13: 9783642249389
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: 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.
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Lingua: Inglese
Editore: World Scientific Publishing Company, 2014
ISBN 10: 9814522287 ISBN 13: 9789814522281
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Aggiungi al carrelloGebunden. Condizione: 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.
Lingua: Inglese
Editore: Springer, Springer Vieweg Jan 2012, 2012
ISBN 10: 3642249388 ISBN 13: 9783642249389
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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 assmall deviations, expansions, and quantization of processes. In university teaching, one can build a one-semester advanced course upon these Briefs.¿Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 132 pp. Englisch.
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Aggiungi al carrelloBuch. Condizione: Neu. RANDOM PROCESSES BY EXAMPLE | Lifshits Mikhail | Buch | Gebunden | Englisch | 2014 | World Scientific | EAN 9789814522281 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloBuch. Condizione: 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.