| 1. | Troubles inside the sample space 区内故障 |
| 2. | Initial sample spacing 初始采样间距参数 |
| 3. | Product sample space 积样本空间 |
| 4. | On constructing and optimization of sample spaces in calculation of classical probability 关于古典概率计算中样本空间的构造及优化 |
| 5. | A note on the method for constructing the confidence limits of parameters based on order relation in the sample space 基于样本空间中序关系构造参数置信限方法的一个注记 |
| 6. | In the gain measurement , the sample spacing can be enlarged directly , yet the required maximum remains unchangeable 增益测量时可以将采样间距直接增大,亦可有效地获得所需的最大值。 |
| 7. | As for the undivided linear sample space , the kernel function is needed to map onto another high dimension linear space 对于线性不可分的样本空间,需要寻找核函数,将线性不可分的样本集映射到另一个高维线性空间。 |
| 8. | And find the reason that cause illusion is to choose the sample space wrongly , then explain the importance of choosing the sample space correctly 并分析了导致错觉的原因是错误地选择了样本空间,进而说明正确选择样本空间的重要性。 |
| 9. | In this dissertation , we propose improved genetic algorithm and utilize it to search sample space for classification and evaluation with the best representative subset of training set 本文提出一种改进的遗传算法,利用改进的遗传算法搜索样本空间,将得到的训练集的近似最优代表性子集作为训练集去分类评估集。 |
| 10. | Compared with conventional statistic classifier , the artificial neural network ( ann ) has been developed and applied to remote sensing data classification problem , which does n ' t need suppose parameterized distribution of sample space in advance 与传统统计方法的分类器相比较,人工神经网络法不需要预先假设样本空间的参数化统计分布,正在被越来越普遍的应用于遥感图像分类的研究。 |