Random field representation methods

Version 1.2.5 (15,8 ko) par Felipe
Implementation of EOLE, OSE and K-L (Discrete, Galerkin & Nyström) methods for 1D random fields
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Mise à jour 30 avr. 2021

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Different covariance kernels are defined to illustrate three series expansion methods for 1D random field representation: (i) the 'expansion optimal linear estimator (EOLE)', (ii) the orthogonal series expansion (OSE)', and (iii) the 'Karhunen-Loève (K-L)' methods. The solution of the K-L eigenvalue problem is computed with the Discrete, Nyström and Galerkin methods. The main references are: "Stochastic finite element methods and reliability" by Sudret and Der Kiureghian, and "Stochastic finite elements: a spectral approach" by Ghanem and Spanos.
Several references to equations and useful comments are written in order to provide a better understanding of the codes. The programs estimate the corresponding eigenvalues and eigenvectors of the covariance kernel, and plot several random field realizations, together with the covariance approximation.

Any suggestions, corrections and/or improvements are kindly accepted :-)

Citation pour cette source

Felipe (2024). Random field representation methods (https://www.mathworks.com/matlabcentral/fileexchange/52372-random-field-representation-methods), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2017b
Compatible avec les versions R2021a et ultérieures
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Version Publié le Notes de version
1.2.5

OSE files updated in an effort to fix a typo. Despite the results look better, a minor typo still seems to be present.

1.2.0.0

New version of K-L code:
* example.m re-structured
* renaming the functions
* adding extra check for orthonormality of eigenvectors
* update of Nyström
* efficient gauss_legendre code (large points)

1.0.0.0