Bibliographies thématiques / Singular stochastic partial differential equations

Littérature scientifique sur le sujet « Singular stochastic partial differential equations »

Auteur : Grafiati

Publié le 27 juillet 2024

Mis à jour le 28 juillet 2024

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Articles de revues sur le sujet "Singular stochastic partial differential equations"

Matoussi, A., L. Piozin et A. Popier. « Stochastic partial differential equations with singular terminal condition ». Stochastic Processes and their Applications 127, n^o 3 (mars 2017) : 831–76. http://dx.doi.org/10.1016/j.spa.2016.07.002.

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Corwin, Ivan, et Hao Shen. « Some recent progress in singular stochastic partial differential equations ». Bulletin of the American Mathematical Society 57, n^o 3 (26 septembre 2019) : 409–54. http://dx.doi.org/10.1090/bull/1670.

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Holm, Darryl D., et Tomasz M. Tyranowski. « Variational principles for stochastic soliton dynamics ». Proceedings of the Royal Society A : Mathematical, Physical and Engineering Sciences 472, n^o 2187 (mars 2016) : 20150827. http://dx.doi.org/10.1098/rspa.2015.0827.

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We develop a variational method of deriving stochastic partial differential equations whose solutions follow the flow of a stochastic vector field. As an example in one spatial dimension, we numerically simulate singular solutions (peakons) of the stochastically perturbed Camassa–Holm (CH) equation derived using this method. These numerical simulations show that peakon soliton solutions of the stochastically perturbed CH equation persist and provide an interesting laboratory for investigating the sensitivity and accuracy of adding stochasticity to finite dimensional solutions of stochastic partial differential equations. In particular, some choices of stochastic perturbations of the peakon dynamics by Wiener noise (canonical Hamiltonian stochastic deformations, CH-SD) allow peakons to interpenetrate and exchange order on the real line in overtaking collisions, although this behaviour does not occur for other choices of stochastic perturbations which preserve the Euler–Poincaré structure of the CH equation (parametric stochastic deformations, P-SD), and it also does not occur for peakon solutions of the unperturbed deterministic CH equation. The discussion raises issues about the science of stochastic deformations of finite-dimensional approximations of evolutionary partial differential equation and the sensitivity of the resulting solutions to the choices made in stochastic modelling.

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Ciotir, Ioana, et Jonas M. Tölle. « Nonlinear stochastic partial differential equations with singular diffusivity and gradient Stratonovich noise ». Journal of Functional Analysis 271, n^o 7 (octobre 2016) : 1764–92. http://dx.doi.org/10.1016/j.jfa.2016.05.013.

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Alhojilan, Yazid, Hamdy M. Ahmed et Wafaa B. Rabie. « Stochastic Solitons in Birefringent Fibers for Biswas–Arshed Equation with Multiplicative White Noise via Itô Calculus by Modified Extended Mapping Method ». Symmetry 15, n^o 1 (10 janvier 2023) : 207. http://dx.doi.org/10.3390/sym15010207.

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Stochastic partial differential equations have wide applications in various fields of science and engineering. This paper addresses the optical stochastic solitons and other exact stochastic solutions through birefringent fibers for the Biswas–Arshed equation with multiplicative white noise using the modified extended mapping method. This model contains many kinds of soliton solutions, which are always symmetric or anti-symmetric in space. Stochastic bright soliton solutions, stochastic dark soliton solutions, stochastic combo bright–dark soliton solutions, stochastic combo singular-bright soliton solutions, stochastic singular soliton solutions, stochastic periodic solutions, stochastic rational solutions, stochastic Weierstrass elliptic doubly periodic solutions, and stochastic Jacobi elliptic function solutions are extracted. The constraints on the parameters are considered to guarantee the existence of these stochastic solutions. Furthermore, some of the selected solutions are described graphically to demonstrate the physical nature of the obtained solutions.

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Eddahbi, Mhamed, Omar Kebiri et Abou Sene. « Infinite Horizon Irregular Quadratic BSDE and Applications to Quadratic PDE and Epidemic Models with Singular Coefficients ». Axioms 12, n^o 12 (21 novembre 2023) : 1068. http://dx.doi.org/10.3390/axioms12121068.

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In an infinite time horizon, we focused on examining the well-posedness of problems for a particular category of Backward Stochastic Differential Equations having quadratic growth (QBSDEs) with terminal conditions that are merely square integrable and generators that are measurable. Our approach employs a Zvonkin-type transformation in conjunction with the Itô–Krylov’s formula. We applied our findings to derive probabilistic representation of a particular set of Partial Differential Equations par have quadratic growth in the gradient (QPDEs) characterized by coefficients that are measurable and almost surely continuous. Additionally, we explored a stochastic control optimization problem related to an epidemic model, interpreting it as an infinite time horizon QBSDE with a measurable and integrable drifts.

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Yang, Juan, Jianliang Zhai et Qing Zhou. « The Small Time Asymptotics of SPDEs with Reflection ». Abstract and Applied Analysis 2014 (2014) : 1–13. http://dx.doi.org/10.1155/2014/264263.

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We study stochastic partial differential equations with singular drifts and with reflection, driven by space-time white noise with nonconstant diffusion coefficients under periodic boundary conditions. The existence and uniqueness of invariant measures is established under appropriate conditions. As a byproduct, the Hölder continuity of the solution is obtained. The strong Feller property is also obtained. Moreover, we show large deviation principle.

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Al-Sawalha, M. Mossa, Humaira Yasmin, Rasool Shah, Abdul Hamid Ganie et Khaled Moaddy. « Unraveling the Dynamics of Singular Stochastic Solitons in Stochastic Fractional Kuramoto–Sivashinsky Equation ». Fractal and Fractional 7, n^o 10 (12 octobre 2023) : 753. http://dx.doi.org/10.3390/fractalfract7100753.

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This work investigates the complex dynamics of the stochastic fractional Kuramoto–Sivashinsky equation (SFKSE) with conformable fractional derivatives. The research begins with the creation of singular stochastic soliton solutions utilizing the modified extended direct algebraic method (mEDAM). Comprehensive contour, 3D, and 2D visual representations clearly depict the categorization of these stochastic soliton solutions as kink waves or shock waves, offering a clear description of these soliton behaviors within the context of the SFKSE framework. The paper also illustrates the flexibility of the transformation-based approach mEDAM for investigating soliton occurrence not only in SFKSE but also in a wide range of nonlinear fractional partial differential equations (FPDEs). Furthermore, the analysis considers the effect of noise, specifically Brownian motion, on soliton solutions and wave dynamics, revealing the significant influence of randomness on the propagation, generation, and stability of soliton in complex stochastic systems and advancing our understanding of extreme behaviors in scientific and engineering domains.

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Shen, Hao. « A stochastic PDE approach to large N problems in quantum field theory : A survey ». Journal of Mathematical Physics 63, n^o 8 (1 août 2022) : 081103. http://dx.doi.org/10.1063/5.0089851.

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In this Review, we review some recent rigorous results on large N problems in quantum field theory, stochastic quantization, and singular stochastic partial differential equations (SPDEs) and their mean field limit problems. In particular, we discuss the O( N) linear sigma model on a two- and three-dimensional torus. The stochastic quantization procedure leads to a coupled system of N interacting Φ4 equations. In d = 2, we show uniformity in N bounds for the dynamics and convergence to a mean-field singular SPDE. For large enough mass or small enough coupling, the invariant measures [i.e., the O( N) linear sigma model] converge to the massive Gaussian free field, the unique invariant measure of the mean-field dynamics, in a Wasserstein distance. We also obtain tightness for certain O( N) invariant observables as random fields in suitable Besov spaces as N → ∞, along with exact descriptions of the limiting correlations. In d = 3, the estimates become more involved since the equation is more singular. We discuss in this case how to prove convergence to the massive Gaussian free field. The proofs of these results build on the recent progress of singular SPDE theory and combine many new techniques, such as uniformity in N estimates and dynamical mean field theory. These are based on joint papers with Scott Smith, Rongchan Zhu, and Xiangchan Zhu.

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Ur Rehman, Hamood, Aziz Ullah Awan, Sayed M. Eldin et Ifrah Iqbal. « Study of optical stochastic solitons of Biswas-Arshed equation with multiplicative noise ». AIMS Mathematics 8, n^o 9 (2023) : 21606–21. http://dx.doi.org/10.3934/math.20231101.

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<abstract><p>In many nonlinear partial differential equations, noise or random fluctuation is an inherent part of the system being modeled and have vast applications in different areas of engineering and sciences. This objective of this paper is to construct stochastic solitons of Biswas-Arshed equation (BAE) under the influence of multiplicative white noise in the terms of the Itô calculus. Bright, singular, dark, periodic, singular and combined singular-dark stochastic solitons are attained by using the Sardar subequation method. The results prove that the suggested approach is a very straightforward, concise and dynamic addition in literature. By using Mathematica 11, some 3D and 2D plots are illustrated to check the influence of multiplicative noise on solutions. The presence of multiplicative noise leads the fluctuations and have significant effects on the long-term behavior of the system. So, it is observed that multiplicative noise stabilizes the solutions of BAE around zero.</p></abstract>

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Thèses sur le sujet "Singular stochastic partial differential equations"

Liu, Xuan. « Some contribution to analysis and stochastic analysis ». Thesis, University of Oxford, 2018. http://ora.ox.ac.uk/objects/uuid:485474c0-2501-4ef0-a0bc-492e5c6c9d62.

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The dissertation consists of two parts. The first part (Chapter 1 to 4) is on some contributions to the development of a non-linear analysis on the quintessential fractal set Sierpinski gasket and its probabilistic interpretation. The second part (Chapter 5) is on the asymptotic tail decays for suprema of stochastic processes satisfying certain conditional increment controls. Chapters 1, 2 and 3 are devoted to the establishment of a theory of backward problems for non-linear stochastic differential equations on the gasket, and to derive a probabilistic representation to some parabolic type partial differential equations on the gasket. In Chapter 2, using the theory of Markov processes, we derive the existence and uniqueness of solutions to backward stochastic differential equations driven by Brownian motion on the Sierpinski gasket, for which the major technical difficulty is the exponential integrability of quadratic processes of martingale additive functionals. A Feynman-Kac type representation is obtained as an application. In Chapter 3, we study the stochastic optimal control problems for which the system uncertainties come from Brownian motion on the gasket, and derive a stochastic maximum principle. It turns out that the necessary condition for optimal control problems on the gasket consists of two equations, in contrast to the classical result on ℝ^d, where the necessary condition is given by a single equation. The materials in Chapter 2 are based on a joint work with Zhongmin Qian (referenced in Chapter 2). Chapter 4 is devoted to the analytic study of some parabolic PDEs on the gasket. Using a new type of Sobolev inequality which involves singular measures developed in Section 4.2, we establish the existence and uniqueness of solutions to these PDEs, and derive the space-time regularity for solutions. As an interesting application of the results in Chapter 4 and the probabilistic representation developed in Chapter 2, we further study Burgers equations on the gasket, to which the space-time regularity for solutions is deduced. The materials in Chapter 4 are based on a joint work with Zhongmin Qian (referenced in Chapter 4). In Chapter 5, we consider a class of continuous stochastic processes which satisfy the conditional increment control condition. Typical examples include continuous martingales, fractional Brownian motions, and diffusions governed by SDEs. For such processes, we establish a Doob type maximal inequality. Under additional assumptions on the tail decays of their marginal distributions, we derive an estimate for the tail decay of the suprema (Theorem 5.3.2), which states that the suprema decays in a manner similar to the margins of the processes. In Section 5.4, as an application of Theorem 5.3.2, we derive the existence of strong solutions to a class of SDEs. The materials in this chapter is based on the work [44] by the author (Section 5.2 and Section 5.3) and an ongoing joint project with Guangyu Xi (Section 5.4).

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Martin, Jörg. « Refinements of the Solution Theory for Singular SPDEs ». Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19329.

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Diese Dissertation widmet sich der Untersuchung singulärer stochastischer partieller Differentialgleichungen (engl. SPDEs). Wir entwickeln Erweiterungen der bisherigen Lösungstheorien, zeigen fundamentale Beziehungen zwischen verschiedenen Ansätzen und präsentieren Anwendungen in der Finanzmathematik und der mathematischen Physik. Die Theorie parakontrollierter Systeme wird für diskrete Räume formuliert und eine schwache Universalität für das parabolische Anderson Modell bewiesen. Eine fundamentale Relation zwischen Hairer's modellierten Distributionen und Paraprodukten wird bewiesen: Wir zeigen das sich der Raum modellierter Distributionen durch Paraprodukte beschreiben lässt. Dieses Resultat verallgemeinert die Fourierbeschreibung von Hölderräumen mittels Littlewood-Paley Theorie. Schließlich wird die Existenz von Lösungen der stochastischen Schrödingergleichung auf dem ganzen Raum bewiesen und eine Anwendung Hairer's Theorie zur Preisermittlung von Optionen aufgezeigt.
This thesis is concerned with the study of singular stochastic partial differential equations (SPDEs). We develop extensions to existing solution theories, present fundamental interconnections between different approaches and give applications in financial mathematics and mathematical physics. The theory of paracontrolled distribution is formulated for discrete systems, which allows us to prove a weak universality result for the parabolic Anderson model. This thesis further shows a fundamental relation between Hairer's modelled distributions and paraproducts: The space of modelled distributions can be characterized completely by using paraproducts. This can be seen a generalization of the Fourier description of Hölder spaces. Finally, we prove the existence of solutions to the stochastic Schrödinger equation on the full space and provide an application of Hairer's theory to option pricing.

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Barrasso, Adrien. « Decoupled mild solutions of deterministic evolution problemswith singular or path-dependent coefficients, represented by backward SDEs ». Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLY009/document.

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Cette thèse introduit une nouvelle notion de solution pour des équationsd'évolution non-linéaires déterministes, appellées solutionsmild découplées.Nous revisitons les liens entre équations différentielles rétrogrades(EDSRs) markoviennes browniennes et EDPsparaboliques semilinéaires en montrant que, sous de très faibles hypothèses,les EDSRs produisent une unique solution mild découplée d'une EDP.Nous étendons ce résultat à de nombreuses autres équations déterministestelles que des Pseudo-EDPs, des Equations Intégrales aux Dérivées Partielles(EIDPs), des EDPs à drift distributionnel, ou des E(I)DPs à dépendancetrajectorielle. Les solutions de ces équations sont représentées via des EDSRs qui peuvent être sans martingale de référence, ou dirigées par des martingales cadlag. En particulier, cette thèse résout le problème d'identification,qui consiste, dans le cas classique d'une EDSR markovienne brownienne, à donner un sens analytique au processus Z, second membre de la solution (Y,Z) de l'EDSR. Dans la littérature, Y détermine en général une solution de viscosité de l'équation déterministe et ce problème d'identification n'est résolu que quand cette solution de viscosité a un minimum de régularité. Notre méthode permet de résoudre ce problème même dans le cas général d'EDSRs à sauts (non nécéssairement markoviennes)
This thesis introduces a new notion of solution for deterministic non-linear evolution equations, called decoupled mild solution.We revisit the links between Markovian Brownian Backward stochastic differential equations (BSDEs) and parabolic semilinear PDEs showing that under very mild assumptions, the BSDEs produce a unique decoupled mild solution of some PDE.We extend this result to many other deterministic equations such asPseudo-PDEs, Integro-PDEs, PDEs with distributional drift or path-dependent(I)PDEs. The solutions of those equations are represented throughBSDEs which may either be without driving martingale, or drivenby cadlag martingales. In particular this thesis solves the so calledidentification problem, which consists, in the case of classical Markovian Brownian BSDEs, to give an analytical meaning to the second component Z ofthe solution (Y,Z) of the BSDE. In the literature, Y generally determinesa so called viscosity solution and the identification problem is only solved when this viscosity solution has a minimal regularity.Our method allows to treat this problem even in the case of general (even non-Markovian) BSDEs with jumps

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Barrasso, Adrien. « Decoupled mild solutions of deterministic evolution problemswith singular or path-dependent coefficients, represented by backward SDEs ». Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLY009.

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Hashemi, Seyed Naser. « Singular perturbations in coupled stochastic differential equations ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/NQ65244.pdf.

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Dareiotis, Anastasios Constantinos. « Stochastic partial differential and integro-differential equations ». Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/14186.

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In this work we present some new results concerning stochastic partial differential and integro-differential equations (SPDEs and SPIDEs) that appear in non-linear filtering. We prove existence and uniqueness of solutions of SPIDEs, we give a comparison principle and we suggest an approximation scheme for the non-local integral operators. Regarding SPDEs, we use techniques motivated by the work of De Giorgi, Nash, and Moser, in order to derive global and local supremum estimates, and a weak Harnack inequality.

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Elton, Daniel M. « Hyperbolic partial differential equations with singular coefficients ». Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389210.

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Hofmanová, Martina. « Degenerate parabolic stochastic partial differential equations ». Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2013. http://tel.archives-ouvertes.fr/tel-00916580.

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In this thesis, we address several problems arising in the study of nondegenerate and degenerate parabolic SPDEs, stochastic hyperbolic conservation laws and SDEs with continues coefficients. In the first part, we are interested in degenerate parabolic SPDEs, adapt the notion of kinetic formulation and kinetic solution and establish existence, uniqueness as well as continuous dependence on initial data. As a preliminary result we obtain regularity of solutions in the nondegenerate case under the hypothesis that all the coefficients are sufficiently smooth and have bounded derivatives. In the second part, we consider hyperbolic conservation laws with stochastic forcing and study their approximations in the sense of Bhatnagar-Gross-Krook. In particular, we describe the conservation laws as a hydrodynamic limit of the stochastic BGK model as the microscopic scale vanishes. In the last part, we provide a new and fairly elementary proof of Skorkhod's classical theorem on existence of weak solutions to SDEs with continuous coefficients satisfying a suitable Lyapunov condition.

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Matetski, Kanstantsin. « Discretisations of rough stochastic partial differential equations ». Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/81460/.

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This thesis consists of two parts, in both of which we consider approximations of rough stochastic PDEs and investigate convergence properties of the approximate solutions. In the first part we use the theory of (controlled) rough paths to define a solution for one-dimensional stochastic PDEs of Burgers type driven by an additive space-time white noise. We prove that natural numerical approximations of these equations converge to the solution of a corrected continuous equation and that their optimal convergence rate in the uniform topology (in probability) is arbitrarily close to 1/2 . In the second part of the thesis we develop a general framework for spatial discretisations of parabolic stochastic PDEs whose solutions are provided in the framework of the theory of regularity structures and which are functions in time. As an application, we show that the dynamical �43 model on the dyadic grid converges after renormalisation to its continuous counterpart. This result in particular implies that, as expected, the �43 measure is invariant for this equation and that the lifetime of its solutions is almost surely infinite for almost every initial condition.

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Spantini, Alessio. « Preconditioning techniques for stochastic partial differential equations ». Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82507.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2013.
This thesis was scanned as part of an electronic thesis pilot project.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 149-155).
This thesis is about preconditioning techniques for time dependent stochastic Partial Differential Equations arising in the broader context of Uncertainty Quantification. State-of-the-art methods for an efficient integration of stochastic PDEs require the solution field to lie on a low dimensional linear manifold. In cases when there is not such an intrinsic low rank structure we must resort on expensive and time consuming simulations. We provide a preconditioning technique based on local time stretching capable to either push or keep the solution field on a low rank manifold with substantial reduction in the storage and the computational burden. As a by-product we end up addressing also classical issues related to long time integration of stochastic PDEs.
by Alessio Spantini.
S.M.

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Livres sur le sujet "Singular stochastic partial differential equations"

Cherny, Alexander S., et Hans-Jürgen Engelbert. Singular Stochastic Differential Equations. Berlin, Heidelberg : Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b104187.

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Pardoux, Étienne. Stochastic Partial Differential Equations. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89003-2.

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Holden, Helge, Bernt Øksendal, Jan Ubøe et Tusheng Zhang. Stochastic Partial Differential Equations. New York, NY : Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-89488-1.

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Lototsky, Sergey V., et Boris L. Rozovsky. Stochastic Partial Differential Equations. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58647-2.

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Holden, Helge, Bernt Øksendal, Jan Ubøe et Tusheng Zhang. Stochastic Partial Differential Equations. Boston, MA : Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4684-9215-6.

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Alison, Etheridge, dir. Stochastic partial differential equations. Cambridge : Cambridge University Press, 1995.

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Gérard, Raymond, et Hidetoshi Tahara. Singular Nonlinear Partial Differential Equations. Wiesbaden : Vieweg+Teubner Verlag, 1996. http://dx.doi.org/10.1007/978-3-322-80284-2.

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Gérard, R. Singular nonlinear partial differential equations. Braunschweig : Vieweg, 1996.

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service), SpringerLink (Online, dir. Stochastic Differential Equations. Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011.

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Pardoux, Etienne, et Aurel Rӑşcanu. Stochastic Differential Equations, Backward SDEs, Partial Differential Equations. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05714-9.

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Chapitres de livres sur le sujet "Singular stochastic partial differential equations"

Zhang, Xicheng. « Multidimensional Singular Stochastic Differential Equations ». Dans Stochastic Partial Differential Equations and Related Fields, 391–403. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74929-7_26.

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Gubinelli, Massimiliano, et Nicolas Perkowski. « An Introduction to Singular SPDEs ». Dans Stochastic Partial Differential Equations and Related Fields, 69–99. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74929-7_4.

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Burgeth, Bernhard, Joachim Weickert et Sibel Tari. « Minimally Stochastic Schemes for Singular Diffusion Equations ». Dans Image Processing Based on Partial Differential Equations, 325–39. Berlin, Heidelberg : Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-33267-1_18.

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Marinelli, Carlo, et Luca Scarpa. « On the Well-Posedness of SPDEs with Singular Drift in Divergence Form ». Dans Stochastic Partial Differential Equations and Related Fields, 225–35. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74929-7_12.

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Cherny, Alexander S., et Hans-Jürgen Engelbert. « 1. Stochastic Differential Equations ». Dans Singular Stochastic Differential Equations, 5–25. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31560-5_2.

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Dacorogna, Bernard, et Paolo Marcellini. « The Singular Values Case ». Dans Implicit Partial Differential Equations, 169–203. Boston, MA : Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1562-2_7.

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Agarwal, Ravi P., et Donal O’Regan. « Singular Perturbations ». Dans Ordinary and Partial Differential Equations, 138–44. New York, NY : Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-79146-3_18.

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Langtangen, H. P., et H. Osnes. « Stochastic Partial Differential Equations ». Dans Lecture Notes in Computational Science and Engineering, 257–320. Berlin, Heidelberg : Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-18237-2_7.

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Bovier, Anton, et Frank den Hollander. « Stochastic Partial Differential Equations ». Dans Metastability, 305–21. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24777-9_12.

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Holden, Helge, Bernt Øksendal, Jan Ubøe et Tusheng Zhang. « Stochastic partial differential equations ». Dans Stochastic Partial Differential Equations, 141–91. Boston, MA : Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4684-9215-6_4.

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Actes de conférences sur le sujet "Singular stochastic partial differential equations"

Alexander, Francis J. « Algorithm Refinement for Stochastic Partial Differential Equations ». Dans RAREFIED GAS DYNAMICS : 23rd International Symposium. AIP, 2003. http://dx.doi.org/10.1063/1.1581638.

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Zhang, Lei, Yongsheng Ding, Kuangrong Hao et Tong Wang. « Controllability of impulsive fractional stochastic partial differential equations ». Dans 2013 10th IEEE International Conference on Control and Automation (ICCA). IEEE, 2013. http://dx.doi.org/10.1109/icca.2013.6564989.

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HESSE, CHRISTIAN H. « A STOCHASTIC METHODOLOGY FOR NON-LINEAR PARTIAL DIFFERENTIAL EQUATIONS ». Dans Proceedings of the Fourth International Conference. WORLD SCIENTIFIC, 1999. http://dx.doi.org/10.1142/9789814291071_0044.

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Guo, Zhenwei, Xiangping Hu et Jianxin Liu. « Modelling magnetic field data using stochastic partial differential equations ». Dans International Conference on Engineering Geophysics, Al Ain, United Arab Emirates, 9-12 October 2017. Society of Exploration Geophysicists, 2017. http://dx.doi.org/10.1190/iceg2017-030.

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Grigo, Constantin, et Phaedon-Stelios Koutsourelakis. « PROBABILISTIC REDUCED-ORDER MODELING FOR STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS ». Dans 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering. Athens : Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2017. http://dx.doi.org/10.7712/120217.5356.16731.

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Wang, Guangchen, Zhen Wu et Jie Xiong. « Partial information LQ optimal control of backward stochastic differential equations ». Dans 2012 10th World Congress on Intelligent Control and Automation (WCICA 2012). IEEE, 2012. http://dx.doi.org/10.1109/wcica.2012.6358150.

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Guiaş, Flavius. « Improved stochastic approximation methods for discretized parabolic partial differential equations ». Dans INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2016 (ICCMSE 2016). Author(s), 2016. http://dx.doi.org/10.1063/1.4968683.

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Potsepaev, R., et C. L. Farmer. « Application of Stochastic Partial Differential Equations to Reservoir Property Modelling ». Dans 12th European Conference on the Mathematics of Oil Recovery. Netherlands : EAGE Publications BV, 2010. http://dx.doi.org/10.3997/2214-4609.20144964.

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Kolarova, Edita, et Lubomir Brancik. « Noise Influenced Transmission Line Model via Partial Stochastic Differential Equations ». Dans 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2019. http://dx.doi.org/10.1109/tsp.2019.8769101.

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Liu, Dezhi, et Weiqun Wang. « On the partial stochastic stability of stochastic differential delay equations with Markovian switching ». Dans 2nd International Conference On Systems Engineering and Modeling. Paris, France : Atlantis Press, 2013. http://dx.doi.org/10.2991/icsem.2013.128.

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Rapports d'organisations sur le sujet "Singular stochastic partial differential equations"

Dalang, Robert C., et N. Frangos. Stochastic Hyperbolic and Parabolic Partial Differential Equations. Fort Belvoir, VA : Defense Technical Information Center, juillet 1994. http://dx.doi.org/10.21236/ada290372.

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Sharp, D. H., S. Habib et M. B. Mineev. Numerical Methods for Stochastic Partial Differential Equations. Office of Scientific and Technical Information (OSTI), juillet 1999. http://dx.doi.org/10.2172/759177.

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Jones, Richard H. Fitting Stochastic Partial Differential Equations to Spatial Data. Fort Belvoir, VA : Defense Technical Information Center, septembre 1993. http://dx.doi.org/10.21236/ada279870.

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Chow, Pao-Liu, et Jose-Luis Menaldi. Stochastic Partial Differential Equations in Physical and Systems Sciences. Fort Belvoir, VA : Defense Technical Information Center, novembre 1986. http://dx.doi.org/10.21236/ada175400.

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Webster, Clayton G., Guannan Zhang et Max D. Gunzburger. An adaptive wavelet stochastic collocation method for irregular solutions of stochastic partial differential equations. Office of Scientific and Technical Information (OSTI), octobre 2012. http://dx.doi.org/10.2172/1081925.

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Preston, Leiph, et Christian Poppeliers. LDRD #218329 : Uncertainty Quantification of Geophysical Inversion Using Stochastic Partial Differential Equations. Office of Scientific and Technical Information (OSTI), septembre 2021. http://dx.doi.org/10.2172/1819413.

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Glimm, James, Yuefan Deng, W. Brent Lindquist et Folkert Tangerman. Final report : Stochastic partial differential equations applied to the predictability of complex multiscale phenomena. Office of Scientific and Technical Information (OSTI), août 2001. http://dx.doi.org/10.2172/771242.

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Cornea, Emil, Ralph Howard et Per-Gunnar Martinsson. Solutions Near Singular Points to the Eikonal and Related First Order Non-linear Partial Differential Equations in Two Independent Variables. Fort Belvoir, VA : Defense Technical Information Center, mars 2000. http://dx.doi.org/10.21236/ada640692.

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Webster, Clayton, Raul Tempone et Fabio Nobile. The analysis of a sparse grid stochastic collocation method for partial differential equations with high-dimensional random input data. Office of Scientific and Technical Information (OSTI), décembre 2007. http://dx.doi.org/10.2172/934852.

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Trenchea, Catalin. Efficient Numerical Approximations of Tracking Statistical Quantities of Interest From the Solution of High-Dimensional Stochastic Partial Differential Equations. Fort Belvoir, VA : Defense Technical Information Center, février 2012. http://dx.doi.org/10.21236/ada567709.

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