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Computational uncertainty quantification for random non-autonomous second order linear differential equations via adapted gPC: a comparative case study with random Fröbenius method and Monte Carlo simulation - MaRDI portal

Computational uncertainty quantification for random non-autonomous second order linear differential equations via adapted gPC: a comparative case study with random Fröbenius method and Monte Carlo simulation (Q2419818)

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Computational uncertainty quantification for random non-autonomous second order linear differential equations via adapted gPC: a comparative case study with random Fröbenius method and Monte Carlo simulation
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    Computational uncertainty quantification for random non-autonomous second order linear differential equations via adapted gPC: a comparative case study with random Fröbenius method and Monte Carlo simulation (English)
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    4 June 2019
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    non-autonomous and random dynamical systems
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    computational uncertainty quantification
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    adaptive generalized polynomial chaos
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    stochastic Galerkin projection technique
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    random Fröbenius method
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