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Stochastic Partial Differential Equations with Lévy Noise
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  • Cited by 80
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

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    Huan, Diem Dang and Gao, Hongjun 2015. Controllability of nonlocal second-order impulsive neutral stochastic functional integro-differential equations with delay and Poisson jumps. Cogent Engineering, Vol. 2, Issue. 1, p. 1065585.

    Liu, Yong and Zhai, Jianliang 2015. Time Regularity of Generalized Ornstein–Uhlenbeck Processes with Lévy Noises in Hilbert Spaces. Journal of Theoretical Probability,

    Mao, Wei You, Surong Wu, Xiaoqian and Mao, Xuerong 2015. On the averaging principle for stochastic delay differential equations with jumps. Advances in Difference Equations, Vol. 2015, Issue. 1,

    Menoukeu-Pamen, Olivier 2015. Non-Linear Time-Advanced Backward Stochastic Partial Differential Equations With Jumps. Stochastic Analysis and Applications, Vol. 33, Issue. 4, p. 673.

    Pavlyukevich, Ilya and Riedle, Markus 2015. Non-Standard Skorokhod Convergence of Lévy-Driven Convolution Integrals in Hilbert Spaces. Stochastic Analysis and Applications, Vol. 33, Issue. 2, p. 271.

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Book description

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.


'Summarising, this book is an excellent addition to the literature on stochastic partial differential equations in general and in particular with respect to evolution equations driven by a discontinuous noise. The exposition is self-contained and very well written and, in my opinion, will become a standard tool for everyone working on stochastic evolution equations and related areas.'

Source: Zentralblatt MATH

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