关联白噪声驱动系统的数值模拟算法

Numerical algorithm for cross-correlated white noise from driving systems

采用常规积分算法和随机等价方法分别导出了关联白噪声驱动随机系统的近似的一阶算法和二阶近似算法 .与常规算法比较 ,等价方法避免了一阶非高斯项的出现带来的困难 ,有效地提高了多噪声驱动系统的数值模拟算法的精度 ,为关联白噪声驱动随机系统的各种统计性质的研究提供了一种行之有效的途径 .

The approximate first order algorithm and the second order approximate procedure for stochastic systems driven by cross-correlated white noises are derived by conventional integration and stochastic equivalent methods respectivety. In comparison with the conventional approach, the difficulty arising from the appearance of non-gaussian term is overcome by the equivalent algorithm during the derivation and the accuracy of the numerical method for multi-noise driving systems was promoted. The presented algorithms are a useful approach for the study on the statistical properties in stochastic systems driven by cross-correlated white noise sources.