Theory of Probability and Random Processes
A one-year course in probability theory and the theory of random processes, taught at Princeton University to undergraduate and graduate students, forms the core of the content of this book It is structured in two parts: the first part providing a detailed discussion of Lebesgue integration, Markov...
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| Hlavní autoři: | , |
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| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Vydání: | 2nd ed. 2007. |
| Edice: | Universitext
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| Témata: | |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Poznámka: |
L'impression du document génère 348 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) Version électronique de la seconde édition datant de 2007 |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Theory of probability and random processes, Leonid B. Koralov, Yakov G. Sinai, 2nd edition, 2007, Berlin, Springer, 1 vol. (XI-351 p.), Universitext, 978-3-540-25484-3 • Theory of Probability and Random Processes, Texte imprimé, 9783540809661 |
Obsah:
- 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