| 1. | In many applications , initial error is the most important specification
在许多应用中，初始误差是最重要的特性。 |
| 2. | The gradient vector can be used to construct the initial errors
这时可以对梯度向量本身进行分析，或者用这个梯度向量构造初始误差场。 |
| 3. | 3 . the application of iterative learning control under the condition of zero initial error
零初始误差条件下迭代学习控制在机器人中的应用。 |
| 4. | An important application of linear singular vectors is to make sensitivity study of the numerical model
线性奇异向量的一个主要应用是作数值模式初始误差的敏感性分析。 |
| 5. | Novel d - type and pd - type iterative learning control algorithms proofs of convergence and their application in robot are presented
非零初始误差条件下迭代学习控制在机器人中的应用。 |
| 6. | Different kinds of iterative learning control algorithms under the condition of zero initial error and the non - zero error have been introduced
主要介绍了零初始误差条件下和非零初始误差条件下的迭代学习控制算法。 |
| 7. | Often instrument manufacturers will specify a reference with a tight initial error so they do not have to perform room - temperature systems calibration after assembly
仪器制造商常常先规定基准严格的初始误差，以便组装后的室温系统无需进行校准。 |
| 8. | Linear singular vector represents the direction that initial errors increase fastest during the validity period of tlm . lsvs can be used to construct initial errors in an ensemble prediction system
对于某一给定的范数，在所考虑的时间段内，线性奇异向量代表初始误差线性增长最快的方向。 |
| 9. | But adjoint method and lsv method are based on linear theory and can only describe the development of small perturbations during the validity period of tangent linear model
在计算得到切线性模式的奇异向量后，可以用这些奇异向量构造初始误差。线性奇异向量方法也是一种线性理论，只能描述切线性模式有效时段内小扰动的发展。 |
| 10. | The most important parameters for data acquisition systems design are initial error , output voltage temperature coefficient ( tc ) , thermal hysteresis , noise , and long - term stability of the voltage reference device
对数据采集系统设计最重要的参数是器件的初始误差、输出电压温度系数、热迟滞系数、输出电压噪声、长期稳定度。 |
