Kramers-Moyal分析中的有限采样间隔效应
Finite sampling interval effects in Kramers-Moyal analysis
摘要：
大的采样间隔会影响Kramers-Moyal系数的重建。一种新的方法，这是直接的，非随机和精确的数值精度，可以估计这些有限时间的影响。对于第一次，精确的有限时间效应的特殊情况下，分析描述;生物启发的数值例子也通过数值。这里开发的方法将允许更好地评估朗之万或福克-普朗克模型的数据与大的采样间隔。它也可以用来预测有限时间效应变得显著的采样间隔。
英文摘要：
Large sampling intervals can affect reconstruction of Kramers-Moyal coefficients from data. A new method, which is direct, non-stochastic and exact up to numerical accuracy, can estimate these finite-time effects. For the first time, exact finite-time effects are described analytically for special cases; biologically inspired numerical examples are also worked through numerically. The approach developed here will permit better evaluation of Langevin or Fokker-Planck based models from data with large sampling intervals. It can also be used to predict the sampling intervals for which finite-time effects become significant.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
