Simulation of second-order processes using Karhunen–Loeve expansion

By Kok-Kwang Phoon, S. P. Huang, S. Quek. 2002

262 citations recorded by the source corpus.

Subfields: Environmental Engineering, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7d95be0f99771bb202db20a0ed1dab9aa07735fc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. George Stefanou
2. Hong-wei Huang
3. Kok-Kwang Phoon
4. S. Quek
5. Manolis Papadrakakis
6. V. Dubourg
7. Bruno Sudret
8. Yajun Li

In Management Science and Operations Research

1. George Stefanou
2. Hong-wei Huang
3. Manolis Papadrakakis
4. Kok-Kwang Phoon
5. S. Quek
6. Bruno Sudret
7. V. Dubourg
8. François Deheeger

In Statistics and Probability

1. George Stefanou
2. V. Dubourg
3. Bruno Sudret
4. Hong-wei Huang
5. Manolis Papadrakakis
6. François Deheeger
7. Kok-Kwang Phoon
8. S. Quek

Citations in the corpus

• Uncertainty reduction and sampling efficiency in slope designs using 3D conditional random fields (2016, methodology): “The unconditional random field can be simulated via several methods [37]; for example, interpolated 95 autocorrelation [38], covariance matrix decomposition, discrete Fourier transform or Fast Fourier 96 transform, turning bands, local average subdivision (LAS), and Karhunen–Loeve expansion [39], 97”
• Numerical methods for the discretization of random fields by means of the Karhunen–Loève expansion (2014, unknown): “[23].”
• Simulation of strongly non-Gaussian processes using Karhunen–Loeve expansion (2005, methodology): “The following iterative steps were proposed to compute these unknown K–L distributions [21]:”
• Simulation of non-Gaussian processes using fractile correlation (2004, methodology): “[9] suggested using the Karhunen–Loeve (K–L) expansion with non-Gaussian random variables to produce the desired non-Gaussian process.”
• Implementation of Karhunen-Loeve expansion for simulation using a wavelet-Galerkin scheme (2002, background): “Keywords: Karhunen–Loeve expansion; simulation; Fredholm integral equation; Wavelet-Galerkin; Discrete wavelet transform; Mallat’s tree algorithm; Harr wavelets”
• Metamodel-based importance sampling for structural reliability analysis (2011, methodology): “A so-called wavelet-Galerkin numerical procedure was thus used as detailed in Phoon et al. (2002).”
• Assessment of spectral representation and Karhunen–Loève expansion methods for the simulation of Gaussian stochastic fields (2007, methodology): “Recently, K–L expansion has been directly applied to the simulation of non-Gaussian fields [29].”
• The stochastic finite element method: Past, present and future (2009, methodology): “As in [141], the distortion to the PDF is used as a criterion to determine the need for further iteration.”