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SMATTLAB_svmmu

于 2012-07-10 发布 文件大小:234KB
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代码说明：

  支持向量机的Matlab实现，支持多分类，据有GGUI操作界面，简单易懂易懂，其中包含输入输出数据。 (Support multi-classification support vector machine, the Matlab implementation, according to GGUI operation interface, easy to understand and easy to understand, which contains the input and output data.)

文件列表：

SMATTLAB_svmmu
..............\MATLAB_svm_gui
..............\..............\1.mat,671,2006-05-11

..............\..............\cerror.asv,1509,2006-05-10
..............\..............\cerror.m,1507,2006-05-10
..............\..............\data
..............\..............\....\c2s.m,770,2006-05-10
..............\..............\....\check2ddata.asv,1204,2005-10-15
..............\..............\....\check2ddata.m,1177,2006-05-08
..............\..............\....\created.asv,868,2006-05-08
..............\..............\....\created.m,878,2006-05-09
..............\..............\....\createdata.asv,29214,2006-05-10
..............\..............\....\createdata.m,29214,2006-05-10
..............\..............\....\loadsets.asv,786,2006-05-10
..............\..............\....\loadsets.m,774,2006-05-12
..............\..............\....\loadsets2.m,776,2006-05-10
..............\..............\....\noname.mat,337,2006-05-12
..............\..............\....\plotdata2.m,465,2006-05-07
..............\..............\demosvm.asv,13939,2006-05-30
..............\..............\demosvm.fig,5387,2008-06-01
..............\..............\demosvm.m,14003,2006-06-06
..............\..............\function
..............\..............\........\bsvm2.m,5415,2006-05-11
..............\..............\........\bsvm2.m~,5362,2006-05-10
..............\..............\........\bsvm2_mex.dll,27648,2006-05-10
..............\..............\........\bsvm2_mex.mexglx,75973,2006-05-10
..............\..............\........\mvsvmclass.m,1918,2006-05-10
..............\..............\........\noname.mat,588,2006-05-10
..............\..............\........\oaasvm.asv,4548,2006-05-10
..............\..............\........\oaasvm.m,4550,2006-05-10
..............\..............\........\oaasvm.m~,4471,2006-05-10
..............\..............\........\oaosvm.m,4981,2008-06-03
..............\..............\........\oaosvm.txt,4046,2008-06-02
..............\..............\........\smo.m,3706,2006-05-10
..............\..............\........\smo_mex.dll,13824,2006-05-10
..............\..............\........\smo_mex.mexglx,66277,2006-05-10
..............\..............\........\svmclass.m,2447,2006-05-10
..............\..............\GUI_Designs
..............\..............\...........\Multi_BSVM__L2_soft_margi.fig,8883,2006-05-06
..............\..............\...........\Multi_BSVM__L2_soft_margi.m,6146,2006-05-24
..............\..............\...........\OAA_Multi_C_SVM.asv,5560,2006-05-10
..............\..............\...........\OAA_Multi_C_SVM.fig,8711,2006-05-06
..............\..............\...........\OAA_Multi_C_SVM.m,5560,2006-05-10
..............\..............\...........\OAO_Multi_SVM.asv,5274,2005-08-14
..............\..............\...........\OAO_Multi_SVM.fig,8634,2006-05-11
..............\..............\...........\OAO_Multi_SVM.m,5500,2008-06-03
..............\..............\kernels
..............\..............\.......\kernel.asv,1650,2006-05-12
..............\..............\.......\kernel.c,4074,2006-05-12
..............\..............\.......\kernel.dll,7680,2006-05-12
..............\..............\.......\kernel.m,1623,2006-05-12
..............\..............\.......\kernel.mexglx,60621,2006-05-12
..............\..............\.......\kernelproj.m,2112,2006-05-12
..............\..............\.......\kernelproj_mex.c,3521,2006-05-12
..............\..............\.......\kernelproj_mex.c~,3527,2006-05-12
..............\..............\.......\kernelproj_mex.dll,7680,2006-05-12
..............\..............\.......\kernelproj_mex.mexglx,60725,2006-05-12
..............\..............\.......\kernel_fun.c,3525,2006-05-12
..............\..............\.......\kernel_fun.h,1666,2006-05-12
..............\..............\noname.mat,694,2006-06-08
..............\..............\pentagon.mat,1634,2008-06-02
..............\..............\stprpath.asv,2372,2005-10-15
..............\..............\stprpath.m,2350,2006-05-12
..............\..............\SVM.fig,3894,2006-05-08
..............\..............\SVM.m,6405,2006-06-05
..............\..............\visual
..............\..............\......\fig2jpg.m,890,2006-05-30
..............\..............\......\marker_color.m,645,2006-05-08
..............\..............\......\marker_type.m,617,2006-05-08
..............\..............\......\pboundary.m,3647,2006-05-10
..............\..............\......\ppatterns.m,4475,2006-05-10

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  • levinson
    图1为均衡带限信号所引起失真的横向或格型自适应均衡器(其中横向FIR系统长M=11), 系统输入是取值为±1的随机序列，其均值为零；参考信号；信道具有脉冲响应： 式中用来控制信道的幅度失真(W = 2～4, 如取W = 2.9,3.1,3.3,3.5等)，且信道受到均值为零、方差(相当于信噪比为30dB)的高斯白噪声的干扰。试比较基于下列几种算法的自适应均衡器在不同信道失真、不同噪声干扰下的收敛情况(对应于每一种情况,在同一坐标下画出其学习曲线): 1）横向/格-梯型结构LMS算法 2）横向/格-梯型结构RLS算法 并分析其结果。(Figure 1 is a band-limited signal caused balanced horizontal or lattice distortion adaptive equalizer (FIR system in which the lateral length M = 11), the system input is the value of a random sequence of ± 1, mean zero reference signal channel has impulse response: Wherein the amplitude of the distortion for the control channel (W = 2 ~ 4, and so as to take W = 2.9,3.1,3.3,3.5), and subjected to a channel with zero mean and variance (equivalent SNR is 30dB) Gaussian white noise. Compare the following types of algorithm-based adaptive equalizer in a different channel distortion, the convergence of different noise interference (corresponding to each situation, draw their learning curve in the same coordinate): 1) landscape/grid- LMS algorithm ladder structure 2) landscape/grid- RLS algorithm ladder structure And analyze the results.)
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