ISBN: 9781118731536
Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communic… mais…
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Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communic… mais…
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ISBN: 9781118731536
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ISBN: 9781118731536
Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communic… mais…
8, ISBN: 9781118731536
Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communic… mais…
ISBN: 9781118731536
Markov Chains ab 100.99 € als epub eBook: Theory and Applications. Aus dem Bereich: eBooks, Belletristik, Erzählungen, https://media.hugendubel.de/shop/coverscans/212/21240106_21240106_bi… mais…
2013, ISBN: 9781118731536
Theory and Applications, [ED: 1], 1. Auflage, eBook Download (EPUB,PDF), eBooks, [PU: John Wiley & Sons]
ISBN: 9781118731536
Markov Chains ab 100.99 EURO Theory and Applications Medien > Bücher
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Dados detalhados do livro - Markov Chains
EAN (ISBN-13): 9781118731536
ISBN (ISBN-10): 1118731530
Ano de publicação: 2013
Editor/Editora: Wiley, J
Língua: eng/Englisch
Livro na base de dados desde 2012-09-23T18:48:51-03:00 (Sao Paulo)
Página de detalhes modificada pela última vez em 2023-02-21T04:44:15-03:00 (Sao Paulo)
Número ISBN/EAN: 1118731530
Número ISBN - Ortografia alternativa:
1-118-73153-0, 978-1-118-73153-6
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Autor do livro: bruno
Título do livro: markov chains
Dados da editora
Autor: Bruno Sericola
Título: Markov Chains - Theory and Applications
Editora: Wiley-ISTE; John Wiley & Sons
416 Páginas
Ano de publicação: 2013-08-05
Língua: Inglês
112,99 € (DE)
Not available (reason unspecified)
EA; E101; E-Book; Nonbooks, PBS / Mathematik; Angewandte Mathematik; Angewandte Mathematik; Applied Mathematics; Mathematics; Mathematik; Angewandte Mathematik; BB
Preface ix Chapter 1. Discrete-Time Markov Chains 1 1.1. Definitions and properties 1 1.2. Strong Markov property 5 1.3. Recurrent and transient states 8 1.4. State classification 12 1.5. Visits to a state 14 1.6. State space decomposition 18 1.7. Irreducible and recurrent Markov chains 22 1.8. Aperiodic Markov chains 30 1.9. Convergence to equilibrium 34 1.10. Ergodic theorem 41 1.11. First passage times and number of visits 53 1.12. Finite Markov chains 68 1.13. Absorbing Markov chains 70 1.14. Examples 76 1.15. Bibliographical notes 87 Chapter 2. Continuous-Time Markov Chains 89 2.1. Definitions and properties 92 2.2. Transition functions and infinitesimal generator 93 2.3. Kolmogorov's backward equation 108 2.4. Kolmogorov's forward equation 114 2.5. Existence and uniqueness of the solutions 127 2.6. Recurrent and transient states 130 2.7. State classification 137 2.8. Explosion 141 2.9. Irreducible and recurrent Markov chains 148 2.10. Convergence to equilibrium 162 2.11. Ergodic theorem 166 2.12. First passage times 172 2.13. Absorbing Markov chains 184 2.14. Bibliographical notes 190 Chapter 3. Birth-and-Death Processes 191 3.1. Discrete-time birth-and-death processes 191 3.2. Absorbing discrete-time birth-and-deathprocesses 200 3.3. Periodic discrete-time birth-and-death processes 208 3.4. Continuous-time pure birth processes 209 3.5. Continuous-time birth-and-death processes 213 3.6. Absorbing continuous-time birth-and-death processes 228 3.7. Bibliographical notes 233 Chapter 4. Uniformization 235 4.1. Introduction 235 4.2. Banach spaces and algebra 237 4.3. Infinite matrices and vectors 243 4.4. Poisson process 249 4.5. Uniformizable Markov chains 263 4.6. First passage time to a subset of states 273 4.7. Finite Markov chains 275 4.8. Transient regime 276 4.9. Bibliographical notes 286 Chapter 5. Queues 287 5.1. The M/M/1 queue 288 5.2. The M/M/c queue 315 5.3. The M/M/ infinity queue 318 5.4. Phase-type distributions 323 5.5. Markovian arrival processes 326 5.6. Batch Markovian arrival process 342 5.7. Block-structured Markov chains 352 5.8. Applications 370 5.9. Bibliographical notes 380 Appendix 1 Basic Results 381 Bibliography 387 Index 395Outros livros adicionais, que poderiam ser muito similares com este livro:
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