Produktbild: Theory of Probability and Random Processes
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Theory of Probability and Random Processes

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.08.2007

Abbildungen

XI, 358 p.

Verlag

Springer Berlin

Seitenzahl

358

Maße (L/B/H)

23,5/15,5/2 cm

Gewicht

552 g

Auflage

2nd ed. 2007

Sprache

Englisch

ISBN

978-3-540-25484-3

Beschreibung

Rezension

From the reviews of the second edition:"The book is based on a series of lectures taught by the authors at Princeton University and the University of Maryland. The material of the book can be used to support a two-semester course in probability and stochastic processes or, alternatively, two independent one-semester courses in probability and stochastic processes, respectively. … will be found useful by advanced undergraduate and graduate students and by professionals who wish to learn the basic concepts of modern probability theory and stochastic processes." (Vladimir P. Kurenok, Mathematical Reviews, Issue 2008 k)“The text is well written and the concepts and results motivated and explained. Most of the chapters include a section with exercises of varying difficulty. The material of the book has been used by the authors to teach one-year lecture courses at Princeton University and the University of Maryland to advanced undergraduate and graduate students. Summarising, the book is enjoyable and provides a concise well-motivated presentation of the material covered, suitable for lecture courses at an advanced level.” (Evelyn Buckwar, Zentralblatt MATH, Vol. 1181, 2010)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.08.2007

Abbildungen

XI, 358 p.

Verlag

Springer Berlin

Seitenzahl

358

Maße (L/B/H)

23,5/15,5/2 cm

Gewicht

552 g

Auflage

2nd ed. 2007

Sprache

Englisch

ISBN

978-3-540-25484-3

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Theory of Probability and Random Processes
  • Probability Theory.- Random Variables and Their Distributions.- Sequences of Independent Trials.- Lebesgue Integral and Mathematical Expectation.- Conditional Probabilities and Independence.- Markov Chains with a Finite Number of States.- Random Walks on the Lattice ?d.- Laws of Large Numbers.- Weak Convergence of Measures.- Characteristic Functions.- Limit Theorems.- Several Interesting Problems.- Random Processes.- Basic Concepts.- Conditional Expectations and Martingales.- Markov Processes with a Finite State Space.- Wide-Sense Stationary Random Processes.- Strictly Stationary Random Processes.- Generalized Random Processes.- Brownian Motion.- Markov Processes and Markov Families.- Stochastic Integral and the Ito Formula.- Stochastic Differential Equations.- Gibbs Random Fields.