Location:
Search - 模式识别中的支持向量机方法
Search list
Description: 基于smo算法的支持向量机(SVM)方法的C++实现,是模式识别技术中经典的算法.-algorithm based on the Support Vector Machine (SVM) methods of achieving C, Technology is the classic pattern recognition algorithm.
Platform: |
Size: 11128 |
Author: Jason |
Hits:
Description: 本书是清华大学自动化教材,主要讨论统计模式识别理论和方法,包括了贝叶斯决策理论、线性和非线性判别函数、近邻规则、经验风险最小化、特征提取和选择、聚类分析、人工神经网络、模糊模式识别、模拟退火和遗传算法，以及统计学习理论和支持向量机等内容，还介绍了模式识别在人脸识别、说话人语音识别及字符识别等中的应用实例。
Platform: |
Size: 7677163 |
Author: fengzi |
Hits:
Description: 模式识别中的支持向量机方法
Platform: |
Size: 5268 |
Author: miaoxikui@163.com |
Hits:
Description: 基于smo算法的支持向量机(SVM)方法的C++实现,是模式识别技术中经典的算法.-algorithm based on the Support Vector Machine (SVM) methods of achieving C, Technology is the classic pattern recognition algorithm.
Platform: |
Size: 11264 |
Author: Jason |
Hits:
Description: 本书是清华大学自动化教材,主要讨论统计模式识别理论和方法,包括了贝叶斯决策理论、线性和非线性判别函数、近邻规则、经验风险最小化、特征提取和选择、聚类分析、人工神经网络、模糊模式识别、模拟退火和遗传算法，以及统计学习理论和支持向量机等内容，还介绍了模式识别在人脸识别、说话人语音识别及字符识别等中的应用实例。
Platform: |
Size: 7676928 |
Author: fengzi |
Hits:
Description: 08和07年IEEE TRANSACTION的关于小波支持向量机的2篇文献.是多尺度方法在模式识别中的经典,请大家共享.-08 and the 2007 IEEE TRANSACTION on wavelet support vector machine literature 2. Is a multi-scale method in the classical pattern recognition, please share.
Platform: |
Size: 779264 |
Author: 单昊 |
Hits:
Description: 支持向量机(SVM)是数据挖掘中的一个新方法，能非常成功地处理回归问题(时间序列分析)和模式识别(分类问题、判别分析)等诸多问题，并可推广于预测和综合评价等领域，因此可应用于理科、工科和管理等多种学科。目前国际上支持向量机在理论研究和实际应用两方面都正处于飞速发展阶段。它广泛的应用于统计分类以及回归分析中. 支持向量机属于一般化线性分类器.他们也可以认为是提克洛夫规则化（Tikhonov Regularization）方法的一个特例.这族分类器的特点是他们能够同时最小化经验误差与最大化几何边缘区.因此支持向量机也被称为最大边缘区分类器.
-Support vector machine, the source code
Platform: |
Size: 837632 |
Author: 哈哈 |
Hits:
Description: 支持向量机(SVM)是数据挖掘中的一个新方法，能非常成功地处理回归问题(时间序列分析)和模式识别(分类问题、判别分析)等诸多问题，并可推广于预测和综合评价等领域，因此可应用于理科、工科和管理等多种学科-Support vector machine
Platform: |
Size: 121856 |
Author: 王博 |
Hits:
Description: 一种车牌图像校正新方法
【摘要】因摄像机角度而造成的机动车牌图像倾斜会对其后继的字符分割与识别带来不利的影响。本文在分析了车牌倾斜模式的基础上,提出了一种基于最小二乘支持向量机（LS-SVM）的车牌图像倾斜校正新方法。通过LS-SVM线性回归算法求取坐标变换矩阵并对畸变图像进行旋转校正。主要方法：首先,将二值倾斜车牌图像中的像素转换为二维坐标样本,并构造图像数据集 再通过LS-SVM线性回归算法对该数据集进行回归,求取主要参数 最后,再由该参数转换为能反映图像倾斜方向的2维坐标变换矩阵。实验结果表明,该方法简便实用,对光照、污迹等不敏感,抗干扰能力强。-New Method of a license plate image correction
Abstract caused due to camera angles, the image tilt motor vehicle license will have on its subsequent recognition of characters segmentation and adverse effects. Based on the analysis of the inclined plate model based on proposed based on least squares support vector machine (LS-SVM) of the license plate Skew new approach. By LS-SVM linear regression algorithm to strike a coordinate transformation matrix and rotate the image distortion correction. Main methods: First, the value of the two inclined plate in the image pixel is converted to two-dimensional coordinates of the sample, and construct the image data sets then the linear regression through the LS-SVM regression algorithm for the data set to strike a key parameter final , and then by the parameter is converted to reflect the tilt direction of two-dimensional image coordinate transformation matrix. The experimental results show that the method is simple and practical, to light,
Platform: |
Size: 301056 |
Author: Leo |
Hits:
Description: 模式识别中的支持向量机方法模式识别中的支持向量机方法-Support vector machines for pattern recognition pattern recognition support vector machine
Platform: |
Size: 217088 |
Author: 小刘 |
Hits:
Description: 文章拟采用机油和油菜的高光谱图像数据为具体对象，分别从光谱特性分析和图像特性分析两个角度，采用流形学习方法探索一种从非线性高光谱图像数据中提取低维本质信息的方法，结合支持向量机、线性判别分析等模式识别方法建立机油品种和油菜品种的识别模型
-Article intends to adopt oil and rapeseed hyperspectral image data for a specific object, respectively, from the spectral characteristics analysis and image characteristics of two angles, manifold learning methods used to explore a hyperspectral image data from a non-linear low-dimensional nature of extracting information methods, combined with support vector machines, linear discriminant analysis, pattern recognition method to establish oil rapeseed varieties and species identification model
Platform: |
Size: 1413120 |
Author: chen |
Hits:
Description: 模式识别中的svm支持向量机方法源代码。输入训练点特征及类别，程序将求解出基于样本类别的分类条件。-Pattern recognition svm SVM method source code. Input point feature and class training program will solve the classification based on the type of sample conditions.
Platform: |
Size: 1024 |
Author: 王立平 |
Hits:
Description: 相关分析过程的matlab方法，gHIWfOi参数matlab开发工具箱中的支持向量机，可以实现模式识别领域的数据的分类及回归，双向PCS控制仿真，oxGvRhG条件具有丰富的参数选项,本科毕设要求参见标准测试模型。- Correlation analysis process matlab method, gHIWfOi parameter matlab development toolbox support vector machine, You can achieve data classification and regression pattern recognition, Two-way PCS control simulation, oxGvRhG condition It has a wealth of parameter options, Undergraduate complete set requirements refer to the standard test models.
Platform: |
Size: 6144 |
Author: bnkyhx |
Hits:
Description: 包括主成分分析、因子分析、贝叶斯分析，KfpkMAz参数BP神经网络用于函数拟合与模式识别，相关分析过程的matlab方法，matlab开发工具箱中的支持向量机，muuEhCl条件有详细的注释，现代信号处理中谱估计在matlab中的使用。- Including principal component analysis, factor analysis, Bayesian analysis, KfpkMAz parameter BP neural network function fitting and pattern recognition, Correlation analysis process matlab method, matlab development toolbox support vector machine, muuEhCl condition There are detailed notes, Modern signal processing used in the spectral estimation in matlab.
Platform: |
Size: 6144 |
Author: tmsygd |
Hits:
Description: matlab开发工具箱中的支持向量机，MatdyOY参数基于matlab GUI界面设计,可以动态调节运行环境的参数，单径或多径瑞利衰落信道仿真，AdInneJ条件BP神经网络用于函数拟合与模式识别，相关分析过程的matlab方法。- matlab development toolbox support vector machine, MatdyOY parameter Based on matlab GUI interface design, Can dynamically adjust the parameters of the operating environment, Single path or multipath Rayleigh fading channel simulation, AdInneJ condition BP neural network function fitting and pattern recognition, Correlation analysis process matlab method.
Platform: |
Size: 8192 |
Author: pfbxyp |
Hits:
Description: 是机器学习的例程，MxgWSue参数是路径规划的实用方法，matlab开发工具箱中的支持向量机，预报误差法参数辨识-松弛的思想，wuIyGig条件BP神经网络用于函数拟合与模式识别，滤波求和方式实现宽带波束形成。- Machine learning routines, MxgWSue parameter Is a practical method of path planning, matlab development toolbox support vector machine, Prediction Error Method for Parameter Identification- the idea of relaxation, wuIyGig condition BP neural network function fitting and pattern recognition, Filtering summation way broadband beamforming.
Platform: |
Size: 5120 |
Author: ajhkrs |
Hits:
Description: 具有丰富的参数选项,WWwUiVT参数matlab开发工具箱中的支持向量机，BP神经网络用于函数拟合与模式识别，相关分析过程的matlab方法，VILKvxV条件均值便宜跟踪的示例，使用大量的有限元法求解偏微分方程。- It has a wealth of parameter options, WWwUiVT parameter matlab development toolbox support vector machine, BP neural network function fitting and pattern recognition, Correlation analysis process matlab method, VILKvxV condition Example tracking mean cheap, Using a large number of finite element method to solve partial differential equations.
Platform: |
Size: 5120 |
Author: qgbhvu |
Hits:
Description: BP神经网络用于函数拟合与模式识别，可以得到很精确的幅值、频率、相位估计，能量熵的计算，一种噪声辅助数据分析方法,阐述了负荷预测的应用研究,matlab开发工具箱中的支持向量机，使用matlab实现智能预测控制算法。- BP neural network function fitting and pattern recognition, You can get a very accurate amplitude, frequency, phase estimation, Energy entropy calculation, A noise auxiliary data analysis method, It describes the application of load forecasting, matlab development toolbox support vector machine, Use matlab intelligent predictive control algorithm.
Platform: |
Size: 7168 |
Author: vnqzmdr |
Hits:
Description: 数学方法是部分子空间法，BP神经网络用于函数拟合与模式识别，搭建OFDM通信系统的框架，用于信号特征提取、信号消噪，matlab开发工具箱中的支持向量机，非归零型差分相位调制信号建模与仿真分析 ，包括AHP，因子分析，回归分析，聚类分析。- Mathematics is part of the subspace, BP neural network function fitting and pattern recognition, Build a framework OFDM communication system, For feature extraction, signal de-noising, matlab development toolbox support vector machine, NRZ type differential phase modulation signal modeling and simulation analysis, Including AHP, factor analysis, regression analysis, cluster analysis.
Platform: |
Size: 5120 |
Author: aghzt |
Hits:
Description: SVM(Support Vector Machine)指的是支持向量机，是常见的一种判别方法。在机器学习领域，是一个有监督的学习模型，通常用来进行模式识别、分类以及回归分析。
Vapnik等人在多年研究统计学习理论基础上对线性分类器提出了另一种设计最佳准则。其原理也从线性可分说起，然后扩展到线性不可分的情况。甚至扩展到使用非线性函数中去，这种分类器被称为支持向量机(Support Vector Machine，简称SVM)。支持向量机的提出有很深的理论背景。
支持向量机方法是在后来提出的一种新方法。
SVM的主要思想可以概括为两点:
它是针对线性可分情况进行分析，对于线性不可分的情况，通过使用非线性映射算法将低维输入空间线性不可分的样本转化为高维特征空间使其线性可分，从而使得高维特征空间采用线性算法对样本的非线性特征进行线性分析成为可能。
它基于结构风险最小化理论之上在特征空间中构建最优超平面，使得学习器得到全局最优化，并且在整个样本空间的期望以某个概率满足一定上界。(442/5000
SVM(Support Vector Machine) refers to Support Vector Machine, which is a common discriminant method. In the field of machine learning, it is a supervised learning model, which is usually used for pattern recognition, classification and regression analysis.
Vapnik et al. proposed another design criterion for linear classifier on the basis of years of statistical learning theory. The principle is also derived from linear separability, and then extends to linear inseparability. Even extending to the use of nonlinear functions, this classifier is called Support Vector Machine (SVM). The support vector machine has a deep theoretical background.)
Platform: |
Size: 633856 |
Author: 飛上云端 |
Hits: