Tensor train-Karhunen-Loève expansion: New theoretical and algorithmic frameworks for representing general non-Gaussian random fields

Computer Methods in Applied Mechanics and Engineering ◽

10.1016/j.cma.2020.113121 ◽

2020 ◽

Vol 367 ◽

pp. 113121

Author(s):

Ling-Ze Bu ◽

Wei Zhao ◽

Wei Wang

Keyword(s):

Random Fields ◽

Gaussian Random Fields ◽

Non Gaussian

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Copula-based multiple indicator kriging for non-Gaussian random fields

Spatial Statistics ◽

10.1016/j.spasta.2021.100524 ◽

2021 ◽

pp. 100524

Author(s):

Gaurav Agarwal ◽

Ying Sun ◽

Huixia J. Wang

Keyword(s):

Random Fields ◽

Gaussian Random Fields ◽

Indicator Kriging ◽

Multiple Indicator ◽

Non Gaussian

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Some Non-Gaussian Random Fields

An Innovation Approach to Random Fields ◽

10.1142/9789812565389_0006 ◽

2004 ◽

pp. 85-95

Keyword(s):

Random Fields ◽

Gaussian Random Fields ◽

Non Gaussian

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A biorthogonal decomposition for the identification and simulation of non-stationary and non-Gaussian random fields

Journal of Computational Physics ◽

10.1016/j.jcp.2016.02.067 ◽

2016 ◽

Vol 314 ◽

pp. 1-13 ◽

Cited By ~ 2

Author(s):

I. Zentner ◽

G. Ferré ◽

F. Poirion ◽

M. Benoit

Keyword(s):

Random Fields ◽

Gaussian Random Fields ◽

Biorthogonal Decomposition ◽

Non Gaussian

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Stochastic representation and dimension reduction for non-Gaussian random fields: review and reflection

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-013-0700-7 ◽

2013 ◽

Vol 27 (7) ◽

pp. 1621-1635 ◽

Cited By ~ 12

Author(s):

Heng Li ◽

Dongxiao Zhang

Keyword(s):

Dimension Reduction ◽

Random Fields ◽

Gaussian Random Fields ◽

Stochastic Representation ◽

Non Gaussian

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Numerical Simulation of Non‐Gaussian Random Fields with Prescribed Correlation Structure

Publications of the Astronomical Society of the Pacific ◽

10.1086/322919 ◽

2001 ◽

Vol 113 (786) ◽

pp. 1009-1020 ◽

Cited By ~ 25

Author(s):

Roberto Vio ◽

Paola Andreani ◽

Willem Wamsteker

Keyword(s):

Numerical Simulation ◽

Random Fields ◽

Gaussian Random Fields ◽

Correlation Structure ◽

Non Gaussian

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Inference on dynamic models for non-Gaussian random fields using INLA

Brazilian Journal of Probability and Statistics ◽

10.1214/15-bjps300 ◽

2017 ◽

Vol 31 (1) ◽

pp. 1-23 ◽

Cited By ~ 3

Author(s):

R. X. Cortes ◽

T. G. Martins ◽

M. O. Prates ◽

B. A. Silva

Keyword(s):

Random Fields ◽

Dynamic Models ◽

Gaussian Random Fields ◽

Non Gaussian

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Gaussian and non-Gaussian random fields associated with Markov processes

Journal of Functional Analysis ◽

10.1016/0022-1236(84)90004-1 ◽

1984 ◽

Vol 55 (3) ◽

pp. 344-376 ◽

Cited By ~ 41

Author(s):

E.B Dynkin

Keyword(s):

Markov Processes ◽

Random Fields ◽

Gaussian Random Fields ◽

Non Gaussian

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Model correction factor method for reliability problems involving integrals of non-Gaussian random fields

Probabilistic Engineering Mechanics ◽

10.1016/s0266-8920(01)00031-5 ◽

2002 ◽

Vol 17 (2) ◽

pp. 109-122 ◽

Cited By ~ 5

Author(s):

Paolo Franchin ◽

Ove Ditlevsen ◽

Armen Der Kiureghian

Keyword(s):

Correction Factor ◽

Random Fields ◽

Gaussian Random Fields ◽

Model Correction ◽

Factor Method ◽

Non Gaussian

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Fitting MA models to linear non-Gaussian random fields using higher-order cumulants

Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers ◽

10.1109/acssc.1995.540945 ◽

2002 ◽

Author(s):

J.K. Tugnait

Keyword(s):

Random Fields ◽

Gaussian Random Fields ◽

Higher Order ◽

Higher Order Cumulants ◽

Non Gaussian

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Peak Number Density of Non-Gaussian Random Fields

Physical Review Letters ◽

10.1103/physrevlett.61.267 ◽

1988 ◽

Vol 61 (3) ◽

pp. 267-270 ◽

Cited By ~ 13

Author(s):

Paolo Catelan ◽

Francesco Lucchin ◽

Sabino Matarrese

Keyword(s):

Random Fields ◽

Gaussian Random Fields ◽

Number Density ◽

Peak Number ◽

Non Gaussian

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