Stochastic finite element technique for stochastic one-dimensional time-dependent differential equations with random coefficients.
Saleh, M.M., El-Kalla, I.L., Ehab, M.M. (2007)
Differential Equations & Nonlinear Mechanics
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Displaying similar documents to “Stochastic finite element for structural vibration.”
Stochastic finite element technique for stochastic one-dimensional time-dependent differential equations with random coefficients.
Linear rescaling of the stochastic process
Petr Lachout (1992)
Commentationes Mathematicae Universitatis Carolinae
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Discussion on the limits in distribution of processes under joint rescaling of space and time is presented in this paper. The results due to Lamperti (1962), Weissman (1975), Hudson Mason (1982) and Laha Rohatgi (1982) are improved here.
Elliptic equations of higher stochastic order
Sergey V. Lototsky, Boris L. Rozovskii, Xiaoliang Wan (2010)
ESAIM: Mathematical Modelling and Numerical Analysis
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This paper discusses analytical and numerical issues related to elliptic equations with random coefficients which are generally nonlinear functions of white noise. Singularity issues are avoided by using the Itô-Skorohod calculus to interpret the interactions between the coefficients and the solution. The solution is constructed by means of the Wiener Chaos (Cameron-Martin) expansions. The existence and uniqueness of the solutions are established under rather weak assumptions, the main...
Identification of stochastic loads applied to a nonlinear dynamical system using an uncertain computational model.
Soize, C., Batou, A. (2008)
Mathematical Problems in Engineering
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On some stochastic parabolic differential equations in a Hilbert space.
El-Nadi, Khairia El-Said (2005)
Journal of Applied Mathematics and Stochastic Analysis
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On solutions of general nonlinear stochastic integral equations.
Balachandran, K., Kim, J.-H. (2006)
Journal of Applied Mathematics and Stochastic Analysis
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Symbolic computing in probabilistic and stochastic analysis
Marcin Kamiński (2015)
International Journal of Applied Mathematics and Computer Science
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The main aim is to present recent developments in applications of symbolic computing in probabilistic and stochastic analysis, and this is done using the example of the well-known MAPLE system. The key theoretical methods discussed are (i) analytical derivations, (ii) the classical Monte-Carlo simulation approach, (iii) the stochastic perturbation technique, as well as (iv) some semi-analytical approaches. It is demonstrated in particular how to engage the basic symbolic tools implemented...
Efficiency of the Stochastic Approximation Method
M. Japundžić (2012)
The Yugoslav Journal of Operations Research
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Regularity of solutions to stochastic Volterra equations
Anna Karczewska, Jerzy Zabczyk (2000)
Atti della Accademia Nazionale dei Lincei. Classe di Scienze Fisiche, Matematiche e Naturali. Rendiconti Lincei. Matematica e Applicazioni
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We study regularity of stochastic convolutions solving Volterra equations on driven by a spatially homogeneous Wiener process. General results are applied to stochastic parabolic equations with fractional powers of Laplacian.