Multi-level stochastic refinement for complex time series and fields: a data-driven approach
Spatio-temporally extended nonlinear systems often exhibit a remarkable complexity in space and time. In many cases, extensive datasets of such systems are difficult to obtain, yet needed for a range of applications. Here, we present a method to generate synthetic time series or fields that reproduc...
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Veröffentlicht in: | New journal of physics 2021-06, Vol.23 (6), p.63063, Article 063063 |
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Format: | Artikel |
Sprache: | eng |
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