Detecting intrinsic slow variables in stochastic dynamical systems by anisotropic diffusion maps
Nonlinear independent component analysis is combined with diffusion-map data analysis techniques to detect good observables in high-dimensional dynamic data. These detections are achieved by integrating local principal component analysis of simulation bursts by using eigenvectors of a Markov matrix...
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| Aineistotyyppi: | Journal article |
| Julkaistu: |
PNAS
2009
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Detecting intrinsic slow variables in stochastic dynamical systems by anisotropic diffusion maps.
Julkaistu 2009
Journal article