本文主要研究目前较为流行的基于统计学习理论的分类方法——支持向量机方法(SVM)，以及小波变换提取特征的方法，将其用于人脸检测。
This paper mainly make research on classify methods based on statistical theory, support vector machine (SVM), and feature extraction method-wavelet transform, and using them in human face detection.
支持向量机是一种基于统计学习理论的新型机器学习方法，它可以被广泛地用于非线性系统建模。
Support vector machine (SVM) is a brand-new machine learning technique based on statistical learning theory. It is an ideal facility for modeling of various nonlinear systems.
支持向量机(SVM)是基于统计学习理论的新一代机器学习技术。
Support vector machine (SVM) is a new generation machine learning technique based on the statistical learning theory.
支持向量机是基于统计学习理论框架下的一种简单、有效的分类方法。
Support Vector Machines algorithm is a simple and effective classification method based upon statistical learning theory.
基于支持向量机的直推式学习是统计学习理论中一个较新的研究领域。
Transductive inference based on support vector machine is a relatively new research region in statistical learning theory.
支持向量机是基于VC维和统计学习理论理念的数据挖掘中的一种新方法。
Support Vector Machine is a new method based on the idea of VC dimension and Statistical Learning Theory in data mining.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Support vector machines (SVM) are a kind of novel machine learning methods, based on statistical learning theory, which have been developed for solving classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Support vector machines (SVM) are a kind of novel machine learning methods based on statistical learning theory, which has been developed to solve classification and regression problems.
支持向量机是基于统计学习理论的一种新的机器学习方法。
Support Vector machine is a kind of new machine studying method, which is based on Statistical Learning Theory.
为此，结合统计学习理论的研究成果，建立了基于最小一乘准则的最优回归模型，并将其应用于商业银行的信贷风险评估中。
Thus, combined with research results of statistic learning theory, the optimal regress model based on least-absolute criteria, or LaOR model was proposed to solve the problem.
基于统计学习理论中结构风险最小化原则的支持向量机是易于小样本的机器学习方法。
Support vector machine (SVM) based on the structural risk minimization of statistical learning theory is a method of machine learning for small sample set.
支持向量机是一种基于统计学习理论的新型机器学习方法。
Support vector machine (SVM) is a new learning machine based on the statistical learning theory.
建立在统计学习理论基础之上的支持向量机(SVM)，是一种基于结构风险最小的小样本机器学习方法。
Support vector machine (SVM) is a novel and powerful learning method which is derived based on statistical learning theory (SLT) and the structural risk minimization principle.
在分类器的设计上，重点讨论了最近邻分类器和基于统计学习理论的支持向量机(SVM)。
We emphases discussed the nearest neighbor classifier and support vector machine (SVM) based on the statistical study theory.
基于统计学习理论的支持向量机便是一个典型的例子。
Support vector machines based on statistical learning theory is a typical example.
基于统计学习理论的支持向量机是一类新型的机器学习算法，由于它出色的学习性能，该技术已经成为当前学术界的研究热点。
The support vector machine based on statistical learning is a new type of machine learning algorithm, which has become the hot spot of academic study because of its excellent learning performance.
支持向量机是一种基于统计学习理论的新型学习机。
The support vector machine (SVM) is a new learning machine based on the statistical learning theory.
支持向量机是一种基于统计学习理论的机器学习方法，它解决了神经网络中存在的一系列问题。
Support Vector Machine(SVM) is a machine learning method based on Statistical Learning Theory. It can solve a series of issues of Neural Networks.
支持向量机是一种基于统计学习理论的机器学习算法，能够较好地解决小样本的学习问题。
As one algorithm of the machine learning based on the statistical learning theory, Support Vector machine (SVM) is specifically to the small samples learning case.
支持向量机是一种基于统计学习理论的机器学习方法，该理论主要研究在有限样本下的学习问题。
Support vector machine is a kind of machine learning algorithm based on statistical learning theory which mainly researches the learning of limited number of samples.
支持向量机(SVM)是基于统计学习理论的一种智能学习方法，可以用来解决样本空间的高度非线性的模式识别等问题。
Support Vector Machine (SVM) is an intellectual learning method based on the statistics theory. The SVM can solve problems of complicated nonlinear pattern recognition of spatial samples.
基于统计学习理论的支持向量机是当前机器学习领域的一个研究热点。
Currently, the support vector machine (SVM) which based on statistical learning theory is a research hotspot.
支持向量机是基于统计学习理论的新一代机器学习技术。
This dissertation firstly describes the theoretical bases of SVM-statistical learning theory (SLT).
基于统计学习理论的支持向量机是一种新型机器学习工具。
Support vector machines (SVM) based on the statistical learning theory is a new machine learning tool.
最后证明基于双重随机样本的统计学习理论的关键定理并讨论学习过程一致收敛速度的界。
Finally the key theorem of statistical learning theory based on random rough samples is proved, and the bounds on the rate of uniform convergence of learning process are discussed.
本文采用统计学习理论，建立了基于最小二乘支持向量机的永磁操动机构动作时间预测模型。
Support vector machine (SVM) is the best general machine learning theory developed from statistical learning theory, and suit to do prediction from small samples by learning.
本文采用统计学习理论，建立了基于最小二乘支持向量机的永磁操动机构动作时间预测模型。
Support vector machine (SVM) is the best general machine learning theory developed from statistical learning theory, and suit to do prediction from small samples by learning.
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