Equivalent random force and time‐series model in systems far from equilibrium
Equivalent random force and time‐series model in systems far from equilibrium
复制标题
远离平衡系统中的等效随机力和时间序列模型
DOI：
10.1063/1.526287
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发表时间：
1984
期刊：
影响因子：
--
通讯作者：
K. Kishida
中科院分区：
文献类型：
--
作者：
K. Kishida
在给定观测时间序列数据的条件下，物理系统的随机马尔可夫方程可以转化为用于时间序列分析的可观测非马尔可夫方程。在推导观测变量的时间序列模型时，满足涨落耗散定理的物理随机力也被转化为随机等效随机力。统计量，即，可观测变量的相关函数和功率谱密度函数，既可用物理随机力表示，也可用等效随机力表示。还找到了物理随机力方差与等效随机力方差之间的关系。
Under the condition that observed time‐series data is given, a stochastic Markovian equation for a physical system can be transformed into an observable non‐Markovian equation used in the time‐series analysis. The physical random force satisfying the fluctuation dissipation theorem is also transformed into a stochastically equivalent random force in the derivation of the time‐series model of observable variables. Statistical quantities, i.e., correlation and power spectral density functions for observable variables, can be expressed not only by the physical random force, but also by the equivalent random force. A relation between the variance of physical random force and that of equivalent random force is also found.