通过基于重要性采样和蒙特卡罗模拟方法得到一高斯分布来近似未知状态变量的后验分布。
A single Gaussian distribution is obtained to approximate the posterior distribution of state parameters based on sequential importance sampling and Monte Carlo methods.
采用蒙特卡罗方法研究高斯噪声场对添加硬球粒子的二元混合物系统自组装的驱动作用。
We study orderd structures of binary mixtures with mobile particles under Gaussian noise with Monte Carlo method.
与蒙特卡洛模拟解对比结果表明，该解析解能够较好地预测滑移系统的稳态高斯随机响应。
The results compared with Monte Carlo simulation show that the analytical solutions can well forecast the probability distribution of the steady-state Gaussian responses of the systems.
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