样本问题

ANN can make the best approximation of the actual problems through a large number of learning and training.

人工神经网络方法通过大量的样本学习和训练，能够对实际问题进行最佳逼近。

We have, however, collected the considered views of a lot of people and we think that, even given the problems of a biased sample, they give valid information and lead to conclusions that could guide useful research and give a wake-up call to teachers and parents of left-handed children.

不过，我们已收集了审议意见，有很多人，我们认为，即使考虑到的问题有偏见的样本，他们给有效信息，并导致结论可以指导有益的研究，并敲响了警钟教师和家长的左手儿童。

The main research work in this paper is as follows:(1) A detailed analysis about the theory of the SVM is given in the paper. And one framework of the Network Fault Diagnosis System based on SVM in network Application Layer is proposed. The handle process and the function, mechanism of the components of this framework are discussed in the paper.(2) When the size of the training sets is uneven, the classification error rate of the results based on the traditional C-Support vector machine is undesirably biased with the less sample in the training sets.

由于故障诊断是有限样本学习问题在实际中的体现，因此可以将支持向量机方法引入到网络应用层的故障诊断中来，本文涉及的内容主要包括：(1)详细深入的分析了支持向量机的理论特点及其与网络应用层故障诊断的关联，并就构建的基于支持向量机的网络应用层故障诊断模型，阐述了该模型的处理流程以及其中各个模块的功能、机制。

The algorithm combines active learning, biased classification and incremental learning to model the small sample biased learning problem in relevance feedback process.

该算法将主动式学习、有偏分类和增量学习结合起来，对相关反馈过程中的小样本有偏学习问题进行建模。

For the mapping problems in binary field, a learning algorthm is given to choose better hidden nodes for multilayer feedforward networks, by means of solving maximum separated groups.(7) Expert system for evaluating oil shale is constructed based on neural networks.

改进了前述两种多层前向网络学习算法，使网络的隐节点减少一个；对二值域上的映射问题，通过求解选择样本集极大划分组的手法，给出了一种选择较优隐节点的多层前向网络学习算法。

Sample Size Determination is commonly encountered in modern medical studies and statistical analysis for two independent binomial experiments.

样本容量的确定在现代生物医学研究以及在对两个独立的二项实验进行统计分析时，是经常遇到的一个问题。

So, it is a hotspot that how to effectively recognize the spot on the biochip .

如何有效地识别芯片上的斑点样本也成为生物芯片技术中的一个热点问题。

In some situations, as in the first two examples, it is not a problem because there is not much contrast, but on other situations, when there is strong contrast (eg dark subject against bright background), the fringe is annoying, in particular in the out of focus areas.

在有的情况下，在第一两个例子，这不是一个问题，因为没有太多的对比，但样本）其他situations（本田和阿尔贝托，when有强烈的对比（eg bright background dark主题against），附带特别是恼人的，在地区内的焦点。

This model rank the runoffs firstly and is based on two runoff taxonomies: the fuzzy C mean and the self-organization mapping. However, when the samples on the border of two sorts choose the local neural network models, they tend to make mistakes.

针对分类过程中一些类与类之间的边缘样本在选择局部神经网络模型时出现的误判问题，在上面已经建立的模型的基础上，建立了加入专家经验的模糊逻辑选择模型。

The traditional Canonical Correlation Analysis based image recognition methods always encounter the Small Sample Size problem,which is due to the size of sample and less than the dimension of sample.In order to solve this problem,a new supervised learning method called Two-Dimensional CCA（2DCCA） is developed.

针对传统典型相关分析（Canonical Correlation Analysis，CCA）的图像识别中出现的小样本（Small Sample Size，SSS）问题，提出二维典型相关分析（Two-Dimensional CCA，2DCCA）。

And Pharaoh spoke to Joseph, saying, Your father and your brothers have come to you.

47：5 法老对约瑟说，你父亲和你弟兄们到你这里来了。

Additionally, the approximate flattening of surface strip using lines linking midpoints on perpendicular lines between geodesic curves and the unconditional extreme value method are discussed.

提出了用测地线方程、曲面上两点间短程线来计算膜结构曲面测地线的方法，同时，采用测地线间垂线的中点连线和用无约束极值法进行空间条状曲面近似展开的分析。