提出一种新的神经网络模型—时滞标准神经网络模型(DSNNM)，它由线性动力学系统和有界静态时滞非线性算子连接而成。

A novel neural network model, named delayed standard neural network model (DSNNM), is proposed, which is the interconnection of a linear dynamic system and a bounded static delayed nonlinear operator.

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当动力学模型存在未知的随机系统偏差时，两阶段卡尔曼滤波要优于标准卡尔曼滤波。

The two-stage Kalman filter is excellent than standard Kalman filter in the presence of unknown random bias.

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使用现有的产品数据表达与交换标准STEP只能描述CAD模型几何、拓扑和部分运动学信息，对多刚体动力学特征的描述一直是特征模型中的一个空白。

But there are only basic info of geometry, topology and partial kinematics in the CAD model in STEP. The description on feature of multi-rigid-body dynamics is hardly blank.

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