Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure

Mukam JD, Tambue A (2019)
Computers & Mathematics with Applications 77(10): 2786-2803.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Mukam, Jean DanielUniBi; Tambue, Antoine
Erscheinungsjahr
2019
Zeitschriftentitel
Computers & Mathematics with Applications
Band
77
Ausgabe
10
Seite(n)
2786-2803
ISSN
08981221
Page URI
https://pub.uni-bielefeld.de/record/2958781

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Mukam JD, Tambue A. Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure. Computers & Mathematics with Applications. 2019;77(10):2786-2803.
Mukam, J. D., & Tambue, A. (2019). Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure. Computers & Mathematics with Applications, 77(10), 2786-2803. https://doi.org/10.1016/j.camwa.2019.01.011
Mukam, J. D., and Tambue, A. (2019). Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure. Computers & Mathematics with Applications 77, 2786-2803.
Mukam, J.D., & Tambue, A., 2019. Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure. Computers & Mathematics with Applications, 77(10), p 2786-2803.
J.D. Mukam and A. Tambue, “Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure”, Computers & Mathematics with Applications, vol. 77, 2019, pp. 2786-2803.
Mukam, J.D., Tambue, A.: Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure. Computers & Mathematics with Applications. 77, 2786-2803 (2019).
Mukam, Jean Daniel, and Tambue, Antoine. “Optimal strong convergence rates of numerical methods for semilinear parabolic SPDE driven by Gaussian noise and Poisson random measure”. Computers & Mathematics with Applications 77.10 (2019): 2786-2803.

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