在估计目标状态时，采用了粒子滤波算法，设计了基于自适应表面模型的观测模型；
When estimating the target state, particle filter is adopted, and the observation model is designed based on the adaptive appearance model.
提出一种鲁棒自适应表面模型，该模型中每个像素值的变化过程由一混合高斯分布描述。
A robust and adaptive appearance model is proposed, in which the value of each pixel over time is modeled by a mixture of Gaussians.
模型输出到一个模糊自适应控制器的输入导致的系统，实时地调整工件速度，得到最多的要求的表面粗糙度。
Input of the model outputs into a fuzzy adaptive controller leads to the system to adjust real-timely the workpiece speed, getting the up to the requirements surface roughness.
为了适应非定常流场对网格品质要求较高的特点，网格生成采用了基于几何外形、模型表面曲率为基础的自适应生成及加密方法。
The unsteady flow request a higher quality in grid so in this article the Cartesian grid is generated based on geometric and the body curvature.
为了适应非定常流场对网格品质要求较高的特点，网格生成采用了基于几何外形、模型表面曲率为基础的自适应生成及加密方法。
The unsteady flow request a higher quality in grid so in this article the Cartesian grid is generated based on geometric and the body curvature.
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