Comparison of continuous and discrete-time data-based modeling for hypoelliptic systems
Comparison of continuous and discrete-time data-based modeling for hypoelliptic systems
复制标题
亚椭圆系统连续和离散时间数据建模的比较
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
A. Chorin
中科院分区：
文献类型：
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作者：
F. Lu;Kevin K. Lin;A. Chorin
我们比较了两种方法的预测建模的动力系统在离散时间的部分观测。第一种是在时间上连续的，其中使用数据以随机微分方程的形式推断模型，然后将其离散化以用于数值解。第二种是时间上的离散：推断的模型是可以直接用于计算的时间序列的参数表示。比较是在一个特殊的情况下，其中的意见是已知已获得的hypoelliptical随机微分方程。我们证明了离散时间方法具有更好的预测能力，特别是当数据在时间上相对稀疏时。我们讨论开放的问题以及更广泛的意义的结果。
We compare two approaches to the predictive modeling of dynamical systems from partial observations at discrete times. The first is continuous in time, where one uses data to infer a model in the form of stochastic differential equations, which are then discretized for numerical solution. The second is discrete in time: the model one infers is a parametric representation of a time series that can be directly used for computation. The comparison is performed in a special case where the observations are known to have been obtained from a hypoelliptic stochastic differential equation. We show that the discrete-time approach has better predictive skills, especially when the data are relatively sparse in time. We discuss open questions as well as the broader significance of the results.
DOI：
10.1137/090770527
发表时间：
2009-08
期刊：
SIAM J. Numer. Anal.
影响因子：
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作者：
Jonathan C. Mattingly;A. Stuart;M. Tretyakov
通讯作者：
Jonathan C. Mattingly;A. Stuart;M. Tretyakov