求matlab大神解释一下for n1=1:15 P_train(1,n1)=(P_train(1,n1)-P_min_max(1,1))/(P_min_max(1,2)-P_minP_pix=[ 175.8728234\x0567\x050.380957096\x050.270238095149.5075249\x05113\x050.7558148\x050.370238095155.1104445\x05145\x050.934817771\x050.46547

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$求matlab大神解释一下for n1=1:15 P_train(1,n1)=(P_train(1,n1)-P_min_max(1,1))/(P_min_max(1,2)-P_minP_pix=[ 175.8728234\x0567\x050.380957096\x050.270238095149.5075249\x05113\x050.7558148\x050.370238095155.1104445\x05145\x050.934817771\x050.46547$

求matlab大神解释一下for n1=1:15 P_train(1,n1)=(P_train(1,n1)-P_min_max(1,1))/(P_min_max(1,2)-P_minP_pix=[ 175.8728234\x0567\x050.380957096\x050.270238095149.5075249\x05113\x050.7558148\x050.370238095155.1104445\x05145\x050.934817771\x050.46547
求matlab大神解释一下for n1=1:15 P_train(1,n1)=(P_train(1,n1)-P_min_max(1,1))/(P_min_max(1,2)-P_min
P_pix=[ 175.8728234\x0567\x050.380957096\x050.270238095
149.5075249\x05113\x050.7558148\x050.370238095
155.1104445\x05145\x050.934817771\x050.46547619
151.5008251\x0595\x050.627059291\x050.610714286
163.4778272\x0560\x050.36702225\x050.754761905
219.5723116\x0572\x050.327910197\x050.257142857
176.356725\x05119\x050.674768711\x050.351190476
139.7621988\x05185\x051.323676942\x050.489285714
162.3837191\x05126\x050.775939858\x050.642857143
175.2430455\x0570\x050.399445238\x050.742857143
207.9933893\x0598\x050.471168821\x050.280952381
140.0357097\x05116\x050.828360139\x050.357142857
139.3646297\x05131\x050.939980254\x050.48452381
138.1828499\x05125\x050.904598509\x050.632142857
175.5874268\x0567\x050.381576296\x050.741666667];
t=[1 0 0;1 1 0; 0 1 0; 0 1 1; 0 0 1;1 0 0;1 1 0; 0 1 0; 0 1 1; 0 0 1;1 0 0;1 1 0; 0 1 0; 0 1 1; 0 0 1];
t_train=t';
P_train=P_pix';
P_min_max=minmax(P_train);
for n1=1:15
P_train(1,n1)=(P_train(1,n1)-P_min_max(1,1))/(P_min_max(1,2)-P_min_max(1,1));
P_train(2,n1)=(P_train(2,n1)-P_min_max(2,1))/(P_min_max(2,2)-P_min_max(2,1));
end %%%这是啥意思啊?%%%
net = newff(minmax(P_train),[17,3],{'tansig','logsig'},'trainbfg');
net=init(net);
net.trainparam.epochs=5000;
net.trainparam.show=1000
net.trainparam.goal=1e-7;
net=train(net,P_train,t_train);