sample distribution
英 [ˈsɑːmpl ˌdɪstrɪˈbjuːʃn]
美 [ˈsæmpl ˌdɪstrɪˈbjuːʃn]
样品分布；样本分布；采样分布
英英释义
noun
- items selected at random from a population and used to test hypotheses about the population
双语例句
- In all, the researches are small sample and distribution of a single region. It is lack of the comprehensive study with large scale and multi-centre.
总体上各项研究均为小样本、单一地区的散发研究，缺少多中心大样本的综合研究。 - On the base of the situation in the sample distribution of feather space, it proposes object region extraction algorithm. Thirdly, achieve natural image object discernment system applying the Sparse Coding Theory.
在样本在特征空间分布情况分析基础上，提出对象区域提取算法。之后应用稀疏编码理论，实现自然图像对象识别系统。 - In this paper, suppose that the sample distribution of AR ( p) sequence is an elliptical distribution, or the white noise of AR ( p) sequence is elliptical white noise.
本文中，设AR（p）序列的样本分布为椭球分布，AR（p）序列的噪声为椭球白噪声。 - On the basis of image segmentation, pixels in bubble segmentation region were calibrated. At the meantime, concept of sample distribution statistics was introduced. Moreover, some statistical characteristics, such as the average size of bubbles, variance, skewness and abruptness were extracted.
在图像分割的基础上，对气泡分割区域像素进行标定，引入样本统计分布的概念，提取了气泡平均尺寸、方差、偏斜度及陡峭度等统计特征。 - The first version of this example, located in the webapps/ dwi18n/ multdir/ directory of the sample code distribution, makes use of multiple sets of JSP pages.
示例的第一个版本位于示例代码发行包的webapps/dwi18n/multdir/目录中，它运用了多组JSP页面。 - This algorithm is applied on the computer cluster of the multi-node environment, using FCM to implement a algorithm to adjust the sample distribution, so that multiple classifiers can be trained simultaneously on multiple nodes.
该算法应用在多节点环境的计算机集群上，用FCM算法实现一种样本权重修正算法，使得多节点能够同时训练多个分类器。 - The mean shift algorithm is a nonparametric statistical method for seeking the nearest mode of a point sample distribution.
均值移位算法是一种搜索与样本点分布最相近模式的非参数统计方法。 - Linearized sample cumulative distribution frequency
线性化样本累积分布频数 - By balancing the training samples, dynamically resetting initial weights and adaptively evaluating net scales, some shortcomings of the BP algorithm, such as low convergence speed and high dependency on initial sample distribution are overcome, and the algorithm has become more robust and generic.
通过平衡训练样本数量、动态重置初始权值、评定网络规模等措施，解决了BP算法收敛速度慢、受初始样本分布影响大等缺陷，提高了识别算法的稳健性和泛化能力。 - Incorporating the sample distribution information into the process of feature extraction is beneficial to promote the classification performance of features.
把样本分布信息融于特征提取过程将有助于提高特征的分类能力。