Fast simulation of Gaussian random fields

Abstract Fast Fourier transforms are used to develop algorithms for the fast generation of correlated Gaussian random fields on rectangular regions of . The complexities of the algorithms are derived, simulation results and error analysis are presented.

[1]  Brian D. Ripley,et al.  Stochastic Simulation (Wiley Series in Probability and Statistics) , 2006 .

[2]  Markus Fenn,et al.  Fast fourier transform at nonequispaced nodes and applications , 2005 .

[3]  Gabriele Steidl,et al.  Fast Summation at Nonequispaced Knots by NFFT , 2003, SIAM J. Sci. Comput..

[4]  S. Zienau Quantum Physics , 1969, Nature.

[5]  M. Röckner,et al.  A Concise Course on Stochastic Partial Differential Equations , 2007 .

[6]  T. Teichmann,et al.  Harmonic Analysis and the Theory of Probability , 1957, The Mathematical Gazette.

[7]  J. Zabczyk,et al.  Stochastic Equations in Infinite Dimensions , 2008 .

[8]  Brian D. Ripley,et al.  Stochastic Simulation , 2005 .

[9]  A. Lang Simulation of Stochastic Partial Differential Equations and Stochastic Active Contours , 2007 .

[10]  J. Glimm,et al.  Quantum Physics: A Functional Integral Point of View , 1981 .

[11]  Renaud Keriven,et al.  Stochastic Motion and the Level Set Method in Computer Vision: Stochastic Active Contours , 2006, International Journal of Computer Vision.

[12]  Peter R. Kramer,et al.  Comparative analysis of multiscale Gaussian random field simulation algorithms , 2007, J. Comput. Phys..

[13]  T. Gneiting,et al.  Fast and Exact Simulation of Large Gaussian Lattice Systems in ℝ2: Exploring the Limits , 2006 .

[14]  Steven G. Johnson,et al.  The Design and Implementation of FFTW3 , 2005, Proceedings of the IEEE.

[15]  V. Bally,et al.  STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS , 2007 .