Cycle representations of Markov processes
The cycle representations of Markov processes have been advanced after the publication of the ?rst edition to many directions. One main purpose of these advances was the revelation of wide-ranging interpretations of the - cle decompositions of Markov processes such as homologic decompositions, ortho...
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| Médium: | Livre numérique |
| Jazyk: | Anglais |
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New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Vydání: | 2nd ed. |
| Edice: | Stochastic Modelling and Applied Probability
28 |
| Témata: | |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Description d'après consultation du 16 mars 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Cycle representations of Markov processes, Sophia L. Kalpazidou, 2nd ed., New York, Springer, 2006, 1 vol. (XX-301 p.), Stochastic modelling and applied probability, 0-387-29166-0 • Cycle Representations of Markov Processes, Texte imprimé, 9780387509884 • Cycle Representations of Markov Processes, Texte imprimé, 9781441921215 • Cycle representations of Markov processes, Sophia L. Kalpazidou, 2nd ed., New York, Springer, 2006, 1 vol. (XX-301 p.), Stochastic modelling and applied probability, 0-387-29166-0 |
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| 100 | 1 | |a Kalpazidou, Sophia L. | |
| 245 | 1 | 0 | |a Cycle representations of Markov processes |c Sophia L. Kalpazidou. |
| 250 | |a 2nd ed. | ||
| 260 | |a New York, NY : |b Springer New York. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Stochastic Modelling and Applied Probability |v 28 |x 2197-439X | |
| 500 | |a Description d'après consultation du 16 mars 2011 | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 504 | |a Bibliogr. p. [267]-296. Index | ||
| 505 | 1 | |a Fundamentals of the Cycle Representations of Markov Processes Directed Circuits Genesis of Markov Chains by Circuits: The Circuit Chains Cycle Representations of Recurrent Denumerable Markov Chains Circuit Representations of Finite Recurrent Markov Chains Continuous Parameter Circuit Processes with Finite State Space Spectral Theory of Circuit Processes Higher-Order Circuit Processes Cycloid Markov Processes Markov Processes on Banach Spaces on Cycles The Cycle Measures Wide-Ranging Interpretations of the Cycle Representations of Markov Processes Applications of the Cycle Representations Stochastic Properties in Terms of Circuits Lévy s Theorem Concerning Positiveness of Transition Probabilities The Rotational Theory of Markov Processes | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a The cycle representations of Markov processes have been advanced after the publication of the ?rst edition to many directions. One main purpose of these advances was the revelation of wide-ranging interpretations of the - cle decompositions of Markov processes such as homologic decompositions, orthogonality equations, Fourier series, semigroup equations, disinteg- tions of measures, and so on, which altogether express a genuine law of real phenomena. The versatility of these interpretations is consequently motivated by the existence of algebraic topological principles in the fundamentals of the - clerepresentationsofMarkovprocesses,whicheliberatesthestandardview on the Markovian modelling to new intuitive and constructive approaches. For instance, the ruling role of the cycles to partition the ?nite-dimensional distributions of certain Markov processes updates Poincare s spirit to - scribing randomness in terms of the discrete partitions of the dynamical phase state; also, it allows the translation of the famous Minty s painting lemma (1966) in terms of the stochastic entities. Furthermore, the methods based on the cycle formula of Markov p- cesses are often characterized by minimal descriptions on cycles, which widelyexpressaphilosophicalanalogytotheKolmogoroveanentropicc- plexity. For instance, a deeper scrutiny on the induced Markov chains into smallersubsetsofstatesprovidessimplerdescriptionsoncyclesthanonthe stochastic matrices involved in the taboo probabilities. Also, the rec- rencecriteriaon cyclesimprovepreviousconditionsbased on thestochastic matrices, and provide plenty of examples | ||
| 650 | |a Cycles algébriques | ||
| 650 | |a Markov, processus de | ||
| 776 | 0 | |0 110529308 |t Cycle representations of Markov processes |f Sophia L. Kalpazidou |e 2nd ed. |c New York |n Springer |d 2006 |p 1 vol. (XX-301 p.) |s Stochastic modelling and applied probability |z 0-387-29166-0 | |
| 776 | 0 | |t Cycle Representations of Markov Processes |b Texte imprimé |z 9780387509884 | |
| 776 | 0 | |t Cycle Representations of Markov Processes |b Texte imprimé |z 9781441921215 | |
| 776 | 0 | |0 110529308 |t Cycle representations of Markov processes |f Sophia L. Kalpazidou |e 2nd ed. |c New York |n Springer |d 2006 |p 1 vol. (XX-301 p.) |s Stochastic modelling and applied probability |z 0-387-29166-0 | |
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