clear
clc

%獲取訓(xùn)練樣本點
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feature_num=2;
sample_num=200;
mu?=?[0?1];
sigma=[0.65*0.65?0;?0?0.65*0.65];
mu1?=?[0?1];
mu2?=?[0?-1];
r1_=mvnrnd（mu1sigmasample_num）;
r2_=mvnrnd（mu2sigmasample_num）;
%?axis（[-3?3?-3?3]）;
p_train?=?[r1_;r2_];
p_train??=?p_train‘;
t_train?=?ones（12*sample_num）;
t_train?（sample_num+1:2*sample_num）?=?t_train?（sample_num+1:2*sample_num）?-?1;
plotpv（p_train?t_train）;
t_train?=?ones（12*sample_num）;
t_train?（sample_num+1:2*sample_num）?=?t_train?（sample_num+1:2*sample_num）?+?1;
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%lvq算法對其進行優(yōu)化
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k=2;%隱中心的數(shù)目
%?p_cluster（:1:k）?=?em（p_train（:1:sample_num）?k?feature_num?sample_num）;
%?p_cluster（:k+1:2*k）?=?em（p_train（:sample_num+1:2*sample_num）?k?feature_num?sample_num）;
net_lvq?=?newlvq（minmax（p_train）2*k[.5?.5]0.01‘learnlv‘）;
net_lvq.trainParam.epochs=100;
tc_train?=?ind2vec（t_train）;
net_lvq?=?train（net_lvqp_traintc_train）;
p_cluster?=?net_lvq.IW{11}‘;
t_cluster?=?ones（12*k）;
t_cluster（1k+1:2*k）=t_cluster（1k+1:2*k）-1;
plotpv（p_cluster?t_cluster）;
%?plotpv（p_cluster?t_cluster）;
t_cluster?=?ones（12*k）;
t_cluster（1k+1:2*k）=t_cluster（1k+1:2*k）+1;
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%建立網(wǎng)絡(luò)
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p=p_cluster;
t=t_cluster;

%?p=p_train;
%?t=t_train;

net?=?network;
net.n