Implementation of Karhunen-Loeve expansion for simulation using a wavelet-Galerkin scheme
By Kok-Kwang Phoon, Shuping Huang, S. Quek. 2002
255 citations recorded by the source corpus.
Subfields: Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/b3f1a2dc1e008627458aff412520f9da558630e6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atomic and Molecular Physics, and Optics
- George Stefanou
- Hong-wei Huang
- Dianqing Li
- Manolis Papadrakakis
- Kok-Kwang Phoon
- S. Quek
- Daniel Straub
- Iason Papaioannou
In Computer Vision and Pattern Recognition
- George Stefanou
- Hong-wei Huang
- Dianqing Li
- Manolis Papadrakakis
- Kok-Kwang Phoon
- S. Quek
- Daniel Straub
- Iason Papaioannou
In Signal Processing
- George Stefanou
- Hong-wei Huang
- Dianqing Li
- Manolis Papadrakakis
- Kok-Kwang Phoon
- S. Quek
- Daniel Straub
- Iason Papaioannou
Citations in the corpus
- Assessment of spectral representation and Karhunen–Loève expansion methods for the simulation of Gaussian stochastic fields (2007, methodology): “For an exhaustive description of the method, the reader is referred to [30].”
- The stochastic finite element method: Past, present and future (2009, methodology): “Enhanced methods for the solution of the Fredholm integral equation have been proposed in [140,58,164].”
- Numerical methods for the discretization of random fields by means of the Karhunen–Loève expansion (2014, methodology): “It is applied in [7, 8, 9] for the discretization of the IEVP on one-dimensional domains.”
- Slope reliability analysis considering spatially variable shear strength parameters using a non-intrusive stochastic finite element method (2014, methodology): “, 1986) and the KL expansion (Phoon et al., 2002) can be used to discretize the random field.”
- Simulation of non-Gaussian processes using fractile correlation (2004, methodology): “(1) for the Gaussian case efficiently using a wavelet-Galerkin scheme [13].”
- Simulation of strongly non-Gaussian processes using Karhunen–Loeve expansion (2005, methodology): “(2) can be solved quite efficiently using a waveletGalerkin numerical scheme [11].”
- Response surface methods for slope reliability analysis: Review and comparison (2016, methodology): “…ξ when spatial variability of soil properties is considered, Np realizations of independent or cross-correlated random fields are generated using the Karhunen–Loève expansion technique (e.g., Ghiocel and Ghanem, 2002; Phoon et al., 2002; Ghanem and Spanos, 2003; Vořechovský, 2008; Cho, 2010).”