样本函数

The momentum and polar angle depended position resolution and hit efficiency in each layer of BESmuon detector are calibrated by using cosmic ray and hadron samples.

北京谱仪Ⅱ的μ探测器的位置分辨和击中效率与带电粒子的动量和入射位置有关，利用选取的宇宙线样本和强子样本对μ探测器逐层进行了标度，并利用构造的效率比函数在物理分析中有效地识别μ和强子

Randomized orthogonal table is used to produce the specimens for radical basis function neural network.Self-organizing feature map is used to classify the specimens.

选取模具参数和工艺参数等作为影响冲压成形结果的因素，用正交表和随机法产生径向基函数神经网络的学习样本；利用自组织神经网络对样本进行分类，用有限元网格法反算的毛坯的长度作为神经网络的输出；设计了神经网络流程，定义了神经网络输出与有限元分析数据的相对误差。

For these important and practical problems,sample covariance matrix is an important statistic because many important statistics are functionals of it.When we make statistical inferences,such as estimations and/or hypothesis tests,the sample covariance matrices must be investigated.

以上诸多方面在做估计和假设检验过程中，无不用到大维随机矩阵的处理，尤其是大维样本协方差矩阵的相关性质，因为多元分析中许多重要的统计量都可以表示成样本协方差矩阵的函数。

An on-line blind source separation algorithm of non-stationary mixed signals is presented. The algorithm uses the multiple time-delayed decorrelation and natural gradient rule to obtain the stationary point of the cost function, only a small number of observed samples is needed to minimize the Frobenius norm of the correlation matrices, so the computing cost is low and continuous separation calculation could be realized by on-line operation.

利用一种基于多时延解相关准则的代价函数和自然梯度原则，分别推导出非平稳信号在瞬态线性混合及卷积混合情况下的在线盲分离算法，仅通过对有限个时延样本的相关矩阵进行Frobenius范数最小化运算得到分离矩阵，计算工作量小，无需对样本进行分块处理，可实现对信号的连续跟踪操作。

In each period, without the knowledge of the distribution function of the time between failures and the repair time, the PA estimate of gradient of performance function is put into the stochastic approximation algorithm which recursively optimize the threshold value of the flow control model in a manufacturing system.

在分析过程中，对故障时间和工作时间的分布不做任何假设，利用自适应控制的思想，将整个样本路径依据一定的规则分成有限长的时间段，在每一段时间内用扰动分析估计目标函数的样本导数，然后用随机逼近算法渐进地估计流程控制问题中的最优阈值，从而实现了阈值的自适应控制。

In statistics, a statistic is sufficient for the parameter θ, which indexes the distribution family of the data, precisely when the data's conditional probability distribution, given the statistic's value, no longer depends on θ.

统计量是样本的不带任何未知量的函数，一般而言，统计量所包含的信息比样本要少，但可能这些漏掉的信息是无关紧要的。

Subjective evaluation conclusion sample sets of fusion images are considered as output of fuzzy expectation. Several classical objective evaluation indexes are fuzzed by Gaussian membership function as network input samples.

该模型将融合图像的主观评价结论样本集作为模糊期望输出，并利用高斯隶属度函数将多种典型图像融合客观评价指标进行模糊化，作为网络输入样本。

Several classical objective evaluation indexes are fuzzed by Gaussian membership function as network input samples.Related parameters of evaluation index weight and membership function are generated by network learning.

该模型将融合图像的主观评价结论样本集作为模糊期望输出，并利用高斯隶属度函数将多种典型图像融合客观评价指标进行模糊化，作为网络输入样本。

The dissertation recommends some kinds of methods and measures: such as adjusting the network configuration, connecting value and threshold value by the total value of all stylebooks, adding part of the adjusting value of the last time to the current adjusting value, transforming the stylebooks to standard value, optimizing activation function, appending threshold value to the putout of the nerve cell and so on. Simultaneity, the author brings forward a new method to optimize the model of artificial neural network . It is using the automatically adaptive genetic algorithm to make the network configuration, connecting value and threshold value of artificial neural network better. The method can make the model better and improve the simulating effect and forecasting precision.Genetic algorithm is an arithmetic based on evolution and genetics used to search the optimization .

本文针对人工神经网络应用中存在的上述问题，介绍了各种改进方法与措施：如用所有样本的总效果对网络权值矩阵和阈值向量进行调整、调整量中加入动量项、标准化训练样本数据、优化激励函数以及给神经元的输出值添加偏置量等；同时还提出了一种新的优化人工神经网络模型的方法，即采用自适应遗传算法对人工神经网络模型的网络结构和权值阈值进行全局优化搜索，以提高大坝安全监测人工神经网络模型的拟合成果和预测精度。

This method first maps training data into a high dimensional feature space through kernel function concept in Support Vector Machine and constructs orthogonal space in the feature space. Then it maps the data from feature space into the orthogonal space and computes Fisher criterion based global orthogonal discriminants.

首先应用支持向量机中核函数的概念，将样本隐式地映射到特征空间，然后构造特征空间的正交空间，再将特征空间样本映射到特征空间的正交空间，求解基于Fisher的全局正交鉴别矢量集。

I can not make it blossom and suits me

我不能让树为我开花

When temperatures are above approximately 80 °C discolouration of the raceways or rolling elements is a frequent feature.

当温度高于 80 °C 左右时，滚道或滚动元件褪色是很常见的特征。