Results 141 to 150 of about 53,281 (190)
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Brownian Path Generation and Polynomial Chaos
SIAM Journal on Financial Mathematics, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fox, Jamie, Ökten, Giray
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MODELING EXPERIMENTAL DATA WITH POLYNOMIALS CHAOS
Probability in the Engineering and Informational Sciences, 2018Given a raw data sample, the purpose of this paper is to design a numerical procedure to model this sample under the form of polynomial chaos expansion. The coefficients of the polynomial are computed as the solution to a constrained optimization problem.
Gayrard, Emeline +3 more
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Polynomial Chaos Expansions for Stiff Random ODEs
SIAM Journal on Scientific Computing, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wenjie Shi, Daniel M. Tartakovsky
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Generalized polynomial chaos-informed efficient stochastic Kriging
Journal of Computational Physics, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Che, Yiming, Guo, Ziqi, Cheng, Changqing
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Polynomial Chaos as a Control Variate Method
SIAM Journal on Scientific Computing, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fox, Jamie, Ökten, Giray
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Indirect Measurements Via Polynomial Chaos Observer
Proceedings of the 2006 IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement (AMUEM 2006), 2006This paper proposes an innovative approach to the design of algorithms for indirect measurements based on a polynomial chaos observer (PCO). A PCO allows the introduction and management of uncertainty in the process. The structure of this algorithm is based on the standard closed-loop structure of an observer originally introduced by Luenberger.
Anton H. C. Smith +2 more
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2014
In this chapter we review methods for formulating partial differential equations based on the random field representations outlined in Chap. 2 These include the stochastic Galerkin method, which is the predominant choice in this book, as well as other methods that frequently occur in the literature, e.g., stochastic collocation methods and spectral ...
Mass Per Pettersson +2 more
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In this chapter we review methods for formulating partial differential equations based on the random field representations outlined in Chap. 2 These include the stochastic Galerkin method, which is the predominant choice in this book, as well as other methods that frequently occur in the literature, e.g., stochastic collocation methods and spectral ...
Mass Per Pettersson +2 more
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2014
We show that given any μ > 1, an equilibrium x of a dynamic system $$\displaystyle{ x_{n+1} = f(x_{n}) }$$ (1) can be robustly stabilized by a nonlinear control $$\displaystyle{ u = -\sum _{j=1}^{N-1}\varepsilon _{ j}\left (f\left (x_{n-j+1}\right ) - f\left (x_{n-j}\right )\right ),\,\vert \varepsilon _{j}\vert < 1,\;j = 1,\ldots,N - 1, }
Dmitrishin, Dmitriy +2 more
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We show that given any μ > 1, an equilibrium x of a dynamic system $$\displaystyle{ x_{n+1} = f(x_{n}) }$$ (1) can be robustly stabilized by a nonlinear control $$\displaystyle{ u = -\sum _{j=1}^{N-1}\varepsilon _{ j}\left (f\left (x_{n-j+1}\right ) - f\left (x_{n-j}\right )\right ),\,\vert \varepsilon _{j}\vert < 1,\;j = 1,\ldots,N - 1, }
Dmitrishin, Dmitriy +2 more
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2017
Separation of variables is a powerful idea in the study of partial differential equations, and the polynomial chaos method is a particular implementation of this idea for stochastic equations. While the elementary outcome ω is typically never mentioned explicitly in the notation of random objects, it is a variable that can potentially be separated from
Sergey V. Lototsky, Boris L. Rozovsky
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Separation of variables is a powerful idea in the study of partial differential equations, and the polynomial chaos method is a particular implementation of this idea for stochastic equations. While the elementary outcome ω is typically never mentioned explicitly in the notation of random objects, it is a variable that can potentially be separated from
Sergey V. Lototsky, Boris L. Rozovsky
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Time-dependent generalized polynomial chaos
Journal of Computational Physics, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gerritsma, Marc +3 more
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