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0495896 - ÚGN 2019 RIV CH eng C - Konferenční příspěvek (zahraniční konf.)
Béreš, Michal
Karhunen-Loéve Decomposition of Isotropic Gaussian Random Fields Using a Tensor Approximation of Autocovariance Kernel.
High Performance Computing in Science and Engineering. HPCSE 2017. Cham: Springer, 2018 - (Kozubek, T.), s. 188-202. Lecture Notes in Computer Science, Code 216349, Volume 11087. ISBN 978-3-319-97135-3.
[HPCSE 2017: International Conference on High Performance Computing in Science and Engineering /3./. Karolinka (CZ), 22.05.2017-25.05.2017]
Grant CEP: GA MŠMT LQ1602; GA MŠMT LD15105
Institucionální podpora: RVO:68145535
Klíčová slova: random fields sampling * Karhunen-Loève decomposition * tensor approximation * numerical integration
Obor OECD: Applied mathematics
https://link.springer.com/content/pdf/10.1007%2F978-3-319-97136-0_14.pdf
Trvalý link: http://hdl.handle.net/11104/0288771
Béreš, Michal
Karhunen-Loéve Decomposition of Isotropic Gaussian Random Fields Using a Tensor Approximation of Autocovariance Kernel.
High Performance Computing in Science and Engineering. HPCSE 2017. Cham: Springer, 2018 - (Kozubek, T.), s. 188-202. Lecture Notes in Computer Science, Code 216349, Volume 11087. ISBN 978-3-319-97135-3.
[HPCSE 2017: International Conference on High Performance Computing in Science and Engineering /3./. Karolinka (CZ), 22.05.2017-25.05.2017]
Grant CEP: GA MŠMT LQ1602; GA MŠMT LD15105
Institucionální podpora: RVO:68145535
Klíčová slova: random fields sampling * Karhunen-Loève decomposition * tensor approximation * numerical integration
Obor OECD: Applied mathematics
https://link.springer.com/content/pdf/10.1007%2F978-3-319-97136-0_14.pdf
Trvalý link: http://hdl.handle.net/11104/0288771