Green measures for Markov processes
Kondratiev Y, Da Silva JL (2020)
Methods of Functional Analysis and Topology 26(3): 241-248.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Kondratiev, YuriUniBi;
Da Silva, Jose L.
Einrichtung
Abstract / Bemerkung
In this paper we study Green measures of certain classes of Markov processes. In particular Brownian motion and processes with jump generators with different tails. The Green measures are represented as a sum of a singular and a regular part given in terms of the jump generator. The main technical question is to find a bound for the regular part.
Stichworte
Markov processes;
Green measures;
compound Poisson process;
Brownian;
motion
Erscheinungsjahr
2020
Zeitschriftentitel
Methods of Functional Analysis and Topology
Band
26
Ausgabe
3
Seite(n)
241-248
ISSN
1029-3531
Page URI
https://pub.uni-bielefeld.de/record/2948651
Zitieren
Kondratiev Y, Da Silva JL. Green measures for Markov processes. Methods of Functional Analysis and Topology . 2020;26(3):241-248.
Kondratiev, Y., & Da Silva, J. L. (2020). Green measures for Markov processes. Methods of Functional Analysis and Topology , 26(3), 241-248. doi:10.31392/MFAT-npu26_3.2020.05
Kondratiev, Yuri, and Da Silva, Jose L. 2020. “Green measures for Markov processes”. Methods of Functional Analysis and Topology 26 (3): 241-248.
Kondratiev, Y., and Da Silva, J. L. (2020). Green measures for Markov processes. Methods of Functional Analysis and Topology 26, 241-248.
Kondratiev, Y., & Da Silva, J.L., 2020. Green measures for Markov processes. Methods of Functional Analysis and Topology , 26(3), p 241-248.
Y. Kondratiev and J.L. Da Silva, “Green measures for Markov processes”, Methods of Functional Analysis and Topology , vol. 26, 2020, pp. 241-248.
Kondratiev, Y., Da Silva, J.L.: Green measures for Markov processes. Methods of Functional Analysis and Topology . 26, 241-248 (2020).
Kondratiev, Yuri, and Da Silva, Jose L. “Green measures for Markov processes”. Methods of Functional Analysis and Topology 26.3 (2020): 241-248.
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