分类器设计是模式识别系统中的关键步骤之一。
The classifier design is a key step for pattern recognition systems.
使用感知器准则对给定的两个样本进行分类器设计。
Guidelines for the use of sensor for a given classification in two samples of design.
缺陷图像的特征提取和选择是缺陷分类器设计的前提。
Image features extraction and selection are the premise of the defects classifier built-up.
给出了一种基于支持向量机的数字调制信号分类器设计方法。
A classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification.
提出了一种基于类内类间离散度的最小距离分类器设计方法。
Minimum distance classifier based on between-class and within-class scatter is proposed.
汉字识别中，以往的分类器设计都是以字为单位的“字分类器”。
In Chinese Character Recognition, the classifier was designed as word classifier whose classification unit is a word in the past.
以入侵检测系统中的分类器设计为例，研究分类器训练样本选择问题。
Taking the example of designing classifier in intrusion detection system, the selection of training samples for classifier is studied.
重点按照不同的特征提取和分类器设计方法对表情识别技术进行了综述。
Then current recognition technologies are roughly introduced and classified according to different method of feature extraction and classifier design.
无需传统识别算法中特征提取之后复杂的分类器设计，简化了识别流程。
It does not have to design the complexity classifier in the traditional recognition algorithm after feature extraction, and simplifies the recognition process.
目标噪声特征提取和目标分类器设计是被动声呐目标识别系统的关键技术。
Feature extraction of targets radiated noise and design of targets classifier are key technique of passive sonar target recognition system.
目标噪声特征提取和目标分类器设计是被动声纳目标识别系统的关键技术。
Feature extraction of targets radiated noise and design of targets classifier are key issues of passive sonar target recognition system.
分类是数据挖掘的一项主要任务。分类器设计是决定分类性能的关键素之一。
Classifier design is to determine the classification performance of one of the key elements.
文章对被动声纳目标识别的特征提取、特征选择和分类器设计方面进行了回顾。
The techniques of feature extraction, feature selection and design of classifier for passive sonar target recognition are reviewed.
分类器设计是模式识别系统中的关键步骤之一，它直接影响到系统的分类能力。
The classifier design is a key step for pattern recognition systems, which can effect performance of system.
并利用训练后得到的网络作为分类器设计并实现了一种多级策略的汉字识别系统。
Finallly taking advantage of the trained network model as a classifier, we implemented a multi-level strategy Chinese character recognition system.
在分类器设计方面，通过引入支持矢量机，进一步提高低信噪比下的汉语声调识别率。
On the design of classifier, by introducing support vector machine, Chinese tone recognition rate is improved under low signal noise rate conditions.
压缩特征向量的维数，在较低维特征空间中进行分类器设计是特征选择与提取的目的。
To compress the dimensions of characteristic vector and make the design of classificatory in the characteristic space with lower dimensions is the purpose of characteristic selection and extraction.
对于二维任意的两类特征样本进行分类，特征提取的好坏直接影响到分类器设计和性能。
To distinguish different sample, feature extraction directly influences the design and performance of the classifier.
图象解释是计算机视觉的重要组成部分，它涉及图象处理、分类器设计和逻辑推理等许多领域。
Image interpretation is an important part of computer vision, which is related to many fields such as image processing, classifier designing and logic reasoning.
模式识别问题不仅与表示方法有关，也跟用于在分类器设计各个阶段进行训练和测试的用例集有关。
A pattern recognition problem is not only specified by a representation, but also by the set of examples given for training and evaluating a classifier in various stages.
提出设计树和分类器设计器的概念，分别用于决策树设计过程的控制和决策树节点中的分类器的设计。
The idea of designing tree and classifier designer are proposed to control the design process of decision tree and de-sign the classifier of the node of decision tree.
本文主要工作体现在瞬时参数的提取、模糊特征选择、单个分类器设计和组合分类器设计这四个方面。
The main contribution of this dissertation includes four aspects. They are instantaneous parameters extraction, fuzzy feature selection, single classifier design and combined classifier design.
提出了一种基于最小分类错误(MCE)训练的采用多层感知器(MLP)结构的模式分类器设计方法。
An improved design method on pattern classifier based on multi-layer perceptrons (MLP) by means of minimum classification error (MCE) training was proposed.
第三章主要讨论了分类器设计过程中的特征空间优化设计问题、分类器设计准则、基本方法和判别函数的知识。
The third chapter mainly introduces characteristic space optimization design, the classification's design criterion, the essential method and the knowledge about knowledge function.
在分类器的设计上，本架构使用了三层二分的分类器设计思想，将一个困难的4分问题转化为3个层次上的二分问题。
In the designing of classifier module, we convert a 4 classes classifying problem into 3 binary classify problems by using a hierarchy layer classify architecture.
这里特征提取是人脸识别的关键环节，有效的人脸特征提取方法不仅有助于简化后续的分类器设计，而且能够提高识别率。
Feature extraction is the key to face recognition. An effective feature extraction method not only helps to simplify the classification of follow-up design, but also can enhance the recognition rate.
本文采用的技术包括：皮肤检测、人脸检测、目标区域分割、敏感图像特征提取、分类器设计及过滤器在浏览器上的实现等。
Some key techniques are included, such as skin detection, face detection, object area segmentation, image features extraction, the design of classifier and the implement of filter based on browser.
在分类器设计环节，比较五种核非线性分类器，并根据宽带极化雷达目标散射数据的特点，使用融合分类的方法对目标进行分类。
In classification stage, five kernel-based classifications are used and compared, and fusion methods are designed for wide-band polarimetric radar target classification.
文章提出了一种应用人工神经网络进行入侵检测分类器设计的新方法，即采用多层前向网络的交叉覆盖算法进行入侵检测分类器的设计。
A new method of designing the classifier for intrusion detection is proposed based on neural networks, which is the alternative covering algorithm of multi-layer neural networks.
文章提出了一种应用人工神经网络进行入侵检测分类器设计的新方法，即采用多层前向网络的交叉覆盖算法进行入侵检测分类器的设计。
A new method of designing the classifier for intrusion detection is proposed based on neural networks, which is the alternative covering algorithm of multi-layer neural networks.
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