| 1. | Machine tools ; feeds for machine tools ; nominal values , limiting values , transmission ratios
机床.机床的进给量.标称值极限值传动比 |
| 2. | Machine tools ; on - load speeds for machine tools ; nominal values , limiting values , transmission ratios
机床.机床的负荷转数.标称值极限值传动比 |
| 3. | Measurement of emf of each additional voltage , from the same reference standard , of same nominal value
测量置于同一标准器具中，而标称值相同的每一额外电动势。 |
| 4. | Based the capacitance standards , studies on the calibration for the frequency response of single - port capacitor and the measurement for the frequency response of 4tp resistor are performed . the work is divieded in several parts as follows
在10khz 1mhz的频率范围内,利用开发的传递测量系统,对标称值为0 . 01 f 、 0 . 1 f和1 f四端对固体介质电容器进行频率响应的测量。 |
| 5. | And it is commonly regarded as fault - free when the comparative deviation of component parameters are within 5 % of the nominal value , while in practical operations the allowance range could be set flexibly according to different requirements for the circuit performance
通常认为元件参数的相对偏差绝对值在标称值的5 %范围内为无故障,但实际上元件的容差是可以根据对电路性能的不同要求而灵活设定的。 |
| 6. | In this method , the phase difference between two compared signals that have same nominal frequency can be converted into voltage signal by phase detector . the voltage signal varies linearly with the phase difference and can be displayed or recorded by some instruments
此方法是将两个被比对的标称值相同的标准频率信号之间的相位关系，通过线性鉴相器转换成与它成线性关系的电压信号，并通过相应的设备进行显示纪录。 |
| 7. | The laboratory can provide calibration service for the measurement of the wavelength of any laser having a nominal wavelength of 633 nm . calibration is performed by comparing the wavelength of the laser under test with the wavelength of the standard iodine - stabilized helium - neon laser of the laboratory
本所可为波长标称值为633nm的激光器提供波长测量服务。被测试的激光波长将与本所的标准碘稳频氦氖激光器的波长比对而进行校正。 |
| 8. | Ann methods are feasible for the verification measurements in nuclear safeguards . experimental data sets have been used to study the performance of neural networks involving radial basis function neural network and generalized regression neural network ( grnn ) . the optimization of the parameter spreads have been given and the analysis error of grnn no more than 0 . 2 %
分析结果表明，使用泛化能力较高的混合训练集训练神经网络，网络给出的富集度值与标准样品的标称值之间的相对差异小于13 % ；使用泛化能力相对较弱的分组训练集训练神经网络，网络给出的分析结果的不确定度小于2 % ；使用分组训练集和广义回归神经网络，网络给出的分析结果的不确定度小于0 |
