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Wyszukujesz frazę "stochastic method" wg kryterium: Temat


Wyświetlanie 1-5 z 5
Tytuł:
Symbolic computing in probabilistic and stochastic analysis
Autorzy:
Kamiński, M.
Powiązania:
https://bibliotekanauki.pl/articles/331062.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
probabilistic analysis
stochastic computer method
symbolic computation
analiza probabilistyczna
metoda komputerowa
metoda stochastyczna
obliczenia symboliczne
Opis:
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 in any system to derive the basic equations for the stochastic perturbation technique and how to make an efficient implementation of the semi-analytical methods using an automatic differentiation and integration provided by the computer algebra program itself. The second important illustration is probabilistic extension of the finite element and finite difference methods coded in MAPLE, showing how to solve boundary value problems with random parameters in the environment of symbolic computing. The response function method belongs to the third group, where interference of classical deterministic software with the non-linear fitting numerical techniques available in various symbolic environments is displayed. We recover in this context the probabilistic structural response in engineering systems and show how to solve partial differential equations including Gaussian randomness in their coefficients.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 4; 961-973
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Efficient Numerical Algorithms for Balanced Stochastic Truncation
Autorzy:
Benner, P.
Quintana-Orti, E. S.
Quintana-Orti, G.
Powiązania:
https://bibliotekanauki.pl/articles/908055.pdf
Data publikacji:
2001
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
algorytmy
metoda Newtona
model reduction
stochastic realization
balanced truncation
sign function method
Newton's method
Opis:
We propose an efficient numerical algorithm for relative error model reduction based on balanced stochastic truncation. The method uses full-rank factors of the Gramians to be balanced versus each other and exploits the fact that for large-scale systems these Gramians are often of low numerical rank. We use the easy-to-parallelize sign function method as the major computational tool in determining these full-rank factors and demonstrate the numerical performance of the suggested implementation of balanced stochastic truncation model reduction.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2001, 11, 5; 1123-1150
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Homotopy Approach to Rational Covariance Extension With Degree Constraint
Autorzy:
Enqvist, P.
Powiązania:
https://bibliotekanauki.pl/articles/908061.pdf
Data publikacji:
2001
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
optymalizacja
teoria systemów
stochastic realization theory
rational covariance extension problem
ARMA model design
continuation method
optimization
Opis:
The solutions to the Rational Covariance Extension Problem (RCEP) are parameterized by the spectral zeros. The rational filter with a specified numerator solving the RCEP can be determined from a known convex optimization problem. However, this optimization problem may become ill-conditioned for some parameter values. A modification of the optimization problem to avoid the ill-conditioning is proposed and the modified problem is solved efficiently by a continuation method.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2001, 11, 5; 1173-1201
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Random perturbation of the variable metric method for unconstrained nonsmooth nonconvex optimization
Autorzy:
El Mouatasim, A.
Ellaia, R.
Souza de Cursi, J. E.
Powiązania:
https://bibliotekanauki.pl/articles/908374.pdf
Data publikacji:
2006
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
optymalizacja
zaburzenie stochastyczne
zaburzenie losowe
nonconvex optimization
stochastic perturbation
variable metric method
nonsmooth optimization
generalized gradient
Opis:
We consider the global optimization of a nonsmooth (nondifferentiable) nonconvex real function. We introduce a variable metric descent method adapted to nonsmooth situations, which is modified by the incorporation of suitable random perturbations. Convergence to a global minimum is established and a simple method for the generation of suitable perturbations is introduced. An algorithm is proposed and numerical results are presented, showing that the method is computationally effective and stable.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2006, 16, 4; 463-474
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Random perturbation of the projected variable metric method for nonsmooth nonconvex optimization problems with linear constraints
Autorzy:
El Mouatasim, A.
Ellaia, R.
Souza de Cursi, E.
Powiązania:
https://bibliotekanauki.pl/articles/907785.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
optymalizacja globalna
ograniczenie liniowe
zaburzenie stochastyczne
global optimization
linear constraints
variable metric method
stochastic perturbation
nonsmooth optimization
Opis:
We present a random perturbation of the projected variable metric method for solving linearly constrained nonsmooth (i.e., nondifferentiable) nonconvex optimization problems, and we establish the convergence to a global minimum for a locally Lipschitz continuous objective function which may be nondifferentiable on a countable set of points. Numerical results show the effectiveness of the proposed approach.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2011, 21, 2; 317-329
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

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