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TY  - BOOK
ID  - 7022924
TI  - Stochastic partial differential equations with Lévy noise : an evolution equation approach
AU  - Peszat, Szymon
AU  - Zabczyk, Jerzy
PY  - 2007
VL  - v. 113
SN  - 9780521879897 0521879892 9780511721373 9781107089754 1107089751 9781107096059 1107096057 1139883437 9781139883436 1107101654 9781107101654 1107104084 9781107104082 0511721374
PB  - Cambridge: Cambridge university press,
DB  - UniCat
KW  - Stochastic partial differential equations
KW  - Lévy processes
KW  - Stochastic partial differential equations.
KW  - Lévy processes.
KW  - Équations aux dérivées partielles stochastiques
KW  - Lévy, Processus de
KW  - Lévy processes
KW  - Équations aux dérivées partielles stochastiques
KW  - Lévy, Processus de
KW  - Lévy processes.
KW  - Random walks (Mathematics)
KW  - Banach spaces, Stochastic differential equations in
KW  - Hilbert spaces, Stochastic differential equations in
KW  - SPDE (Differential equations)
KW  - Stochastic differential equations in Banach spaces
KW  - Stochastic differential equations in Hilbert spaces
KW  - Differential equations, Partial
KW  - Levy processes.
UR  - https://www.unicat.be/uniCat?func=search&query=sysid:7022924
AB  - Recent years have seen an explosion of interest in stochastic partial differential equations where the driving noise is discontinuous. In this comprehensive monograph, two leading experts detail the evolution equation approach to their solution. Most of the results appeared here for the first time in book form. The authors start with a detailed analysis of Lévy processes in infinite dimensions and their reproducing kernel Hilbert spaces; cylindrical Lévy processes are constructed in terms of Poisson random measures; stochastic integrals are introduced. Stochastic parabolic and hyperbolic equations on domains of arbitrary dimensions are studied, and applications to statistical and fluid mechanics and to finance are also investigated.  Ideal for researchers and graduate students in stochastic processes and partial differential equations, this self-contained text will also interest those working on stochastic modeling in finance, statistical physics and environmental science. 
ER  -