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Title: Efficient Karhunen-Loève expansions via Legendre-Galerkin discretization and tensor structure (English)
Author: Béreš, Michal
Language: English
Journal: Applications of Mathematics
ISSN: 0862-7940 (print)
ISSN: 1572-9109 (online)
Volume: 70
Issue: 6
Year: 2025
Pages: 941-991
Summary lang: English
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Category: math
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Summary: We develop an efficient framework for Karhunen-Loève expansions of isotropic Gaussian random fields on hyper-rectangular domains. The approach approximates the covariance kernel by a positive mixture of squared-exponentials, fitted via Newton optimization with a theoretically informed initialization; we also provide convergence estimates for this Gaussian-mixture approximation. The resulting separable kernel enables a Legendre-Galerkin discretization with a Kronecker product structure across dimensions, together with submatrices exhibiting even/odd parity. For assembly, we employ a Duffy-type transformation followed by Gaussian quadrature. These structural properties substantially reduce memory usage and arithmetic cost compared with naive formulations. All algorithms and numerical experiments are released in an open-source repository that reproduces every figure and table. For completeness, a concise derivation of the three-term recurrence for Legendre polynomials is included in appendix. (English)
Keyword: Karhunen-Loève expansion
Keyword: Legendre-Galerkin basis
Keyword: separable covariance
Keyword: Gaussian-mixture approximation
Keyword: tensor structure
MSC: 42C05
MSC: 60G15
MSC: 60G60
MSC: 65D30
MSC: 65F15
DOI: 10.21136/AM.2025.0163-25
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Date available: 2025-12-20T07:03:50Z
Last updated: 2025-12-22
Stable URL: http://hdl.handle.net/10338.dmlcz/153230
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