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S200502106_SVM_for_classfication
说明: 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.)
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pathloss
matlab code for path loss model
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clusters4
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ryfs_12_07
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NetCreate1
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rkmccd2
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plot_hht
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sar
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emd_signal_1d
1D empirical mode deomposition implementation in matlab
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FeatureExtract
svd with LDA face recognition feature extraction
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