Description: SVM用于模式识别
整理别人的代码（原来的是英文）所得：
kernel.m用于内积矩阵的计算
svcplot.m用于绘图
svm168.m是主程序
testlin.m是采用线形内积函数的支持向量机应用的 文件
testrbf.m是采用RBF内积函数的支持向量机应用 的 文件
每个文件中都有说明。
仿真平台matlab7.0, 仿真全部通过
将所有文件拷贝到work目录下（注意不要直接将上层文件夹直接拷贝到work目录下，若那样操作，必须在matlab的file菜单中的set path中设置相应的路径）。
打开matlab，在命令窗口中输入 testlin或testrbf 即可查看结果。
-SVM pattern recognition for collating other people's code (the original is in English) from : kernel.m plot within the matrix for the calculation svcplot.m for graphics is the main svm168.m testlin.m procedure is used linear plot function within the SVM application documents testrbf.m RBF is using plot function within the SVM applications each file documents were described. Matlab7.0 simulation platform, all through the simulation of all the documents copied to the work directory (not directly to the attention of the upper folder directly copied to w contex directory, as if the operation, Matlab in the file menu on the set path corresponding set the path). Open Matlab, in the command window or imported testlin testrbf can see the results. Platform: |
Size: 6029 |
Author:郑军 |
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Description: SVM用于模式识别
整理别人的代码（原来的是英文）所得：
kernel.m用于内积矩阵的计算
svcplot.m用于绘图
svm168.m是主程序
testlin.m是采用线形内积函数的支持向量机应用的 文件
testrbf.m是采用RBF内积函数的支持向量机应用 的 文件
每个文件中都有说明。
仿真平台matlab7.0, 仿真全部通过
将所有文件拷贝到work目录下（注意不要直接将上层文件夹直接拷贝到work目录下，若那样操作，必须在matlab的file菜单中的set path中设置相应的路径）。
打开matlab，在命令窗口中输入 testlin或testrbf 即可查看结果。
-SVM pattern recognition for collating other people's code (the original is in English) from : kernel.m plot within the matrix for the calculation svcplot.m for graphics is the main svm168.m testlin.m procedure is used linear plot function within the SVM application documents testrbf.m RBF is using plot function within the SVM applications each file documents were described. Matlab7.0 simulation platform, all through the simulation of all the documents copied to the work directory (not directly to the attention of the upper folder directly copied to w contex directory, as if the operation, Matlab in the file menu on the set path corresponding set the path). Open Matlab, in the command window or imported testlin testrbf can see the results. Platform: |
Size: 6144 |
Author:郑军 |
Hits:
Description: 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含：
1，Analysis of linear discriminant function
2，Feature extraction: Linear Discriminant Analysis
3，Probability distribution estimation and clustering
4，Support Vector and other Kernel Machines-
This section should give the reader a quick overview of the methods implemented in
STPRtool.
• Analysis of linear discriminant function: Perceptron algorithm and multiclass
modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection
of known algorithms solving the Generalized Anderson’s Task.
• Feature extraction: Linear Discriminant Analysis. Principal Component Analysis
(PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis.
• Probability distribution estimation and clustering: Gaussian Mixture
Models. Expectation-Maximization algorithm. Minimax probability estimation.
K-means clustering.
• Support Vector and other Kernel Machines: Sequential Minimal Optimizer
(SMO). Matlab Optimization toolbox based algorithms. Interface to the
SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers.
Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell-
Demyanov-Molozenov algorithm Platform: |
Size: 4271104 |
Author:查日东 |
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Description: KPCA与SVM共同用于人脸识别 SVM提高了分类效果 KPCA是一种借鉴SVM中核函数的一种较好的特征提取方法-KPCA and SVM for face recognition SVM together to improve the classification results from KPCA is a kernel function in SVM a better feature extraction method Platform: |
Size: 224256 |
Author:付赛男 |
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Description: In this paper, we show how support vector machine (SVM) can be
employed as a powerful tool for $k$-nearest neighbor (kNN)
classifier. A novel multi-class dimensionality reduction approach,
Discriminant Analysis via Support Vectors (SVDA), is introduced by
using the SVM. The kernel mapping idea is used to derive the
non-linear version, Kernel Discriminant via Support Vectors (SVKD).
In SVDA, only support vectors are involved to obtain the
transformation matrix. Thus, the computational complexity can be
greatly reduced for kernel based feature extraction. Experiments
carried out on several standard databases show a clear improvement
on LDA-based recognition Platform: |
Size: 2048 |
Author:sofi |
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Description: 在ORL或Yale标准人脸数据库上完成模式识别任务。用PCA与基于核的PCA（KPCA）方法完成人脸图像的重构与识别试验.
-Or Yale in the ORL face database, complete the standard pattern recognition tasks. With the PCA and kernel-based PCA (KPCA) method to complete the reconstruction of face image and recognition test. Platform: |
Size: 1024 |
Author:李海 |
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Description: 基于PSO训练SVM的人脸识别利用支持向量机在学习能力方面表现的良好性能,结合核主元分析特征提取方法,将将其应用于人脸识别中,该方法在实验中表现了良好的识别性能,为人脸识别领域提供了一条新的识别途径 已通过测试。
-Good performance, performance in the ability to learn the use of support vector machines based on PSO training SVM face recognition combined kernel principal component analysis feature extraction method will be applied to the face recognition, the method in experiments demonstrated good recognition performance identify a new pathway for face recognition has been tested. Platform: |
Size: 1098752 |
Author:wgh |
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Description: 提出了一种支持矢量机的汉语声调识别新方法。论文首先在基频和对数能量的基础上，建立了一个适合于支
持矢量机分类的等维声调特征。然后对支持矢量机的多分类策略和不同核函数对声调识别的影响进行了实验研究。
与BP神经网络相比，支持矢量机具有更高的识别率和更强的推广能力。-This paper presents a novel support vector machine based Chinese tone recognition method．A
new tone recognition feature is first ex血acted using the fundamental frequency(FO)and logarithmic
energy．And how to select the method of SVM multi-class classification and kernel function is also discussed
by experiments．Compared with BP neural network，SVM has higher recognition rates and more strong
generalization． Platform: |
Size: 472064 |
Author:沈 |
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Description: 人脸特征提取与识别matlab程序，主要提取了PCA特征、SVM分类和核方法分类等，代码可以直接使用-Face recognition based on PCA features and Kernel methods, which is used in pattern extraction. Platform: |
Size: 14765056 |
Author:沈来信 |
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Description: 本程序使用MATLAAB R2014a 编写，基于PCA_SVM的人脸识别程序。程序包括主成份分析、SVM核函数，并附带了人脸库，使之能够直接调用人脸库图像进行人脸识别-The program uses MATLAAB R2014a written procedure based on recognition of PCA_SVM. Program includes principal component analysis, SVM kernel function, and comes face , so that it can directly call the face image recognition library Platform: |
Size: 4229120 |
Author:月逝天 |
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Search - kernel svm recognition