论文标题
慢速流形在具有$α$ stablelévy噪声的多尺度随机系统的参数估计中的作用
The role of slow manifolds in parameter estimation for a multiscale stochastic system with $α$-stable Lévy noise
论文作者
论文摘要
这项工作是关于具有非高斯$α$稳定的lévy噪声的快速随机系统的参数估计。当观测值仅用于缓慢的组件时，估计系统参数，并且该估计的准确性通过$ p $ p $ p \ in（1，α）$的$ p $ tar，借助随机的慢速歧管近似值来降低系统。由于随机系统的尺寸降低，该方法在计算复杂性和成本方面提供了优势。在数值上说明了此方法，并证实基于还原慢系统的参数估计器是原始系统的真实参数值的良好近似值，请存在一个原型示例。
This work is about parameter estimation for a fast-slow stochastic system with non-Gaussian $α$-stable Lévy noise. When the observations are only available for slow components, a system parameter is estimated and the accuracy for this estimation is quantified by $p$-moment with $p\in(1, α)$, with the help of a reduced system through random slow manifold approximation. This method provides an advantage in computational complexity and cost, due to the dimension reduction in stochastic systems. To numerically illustrate this method, and to corroborate that the parameter estimator based on the reduced slow system is a good approximation for the true parameter value of the original system, a prototypical example is present.
