>> net=train(net,pn,tn);

??? Error using ==> trainlm at 109

Output data size does not match net.outputs{2}.size.

Error in ==> network.train at 107

[net,tr] = feval(net.trainFcn,net,X,T,Xi,Ai,EW,net.trainParam);

一运行上面的语句就出错，以下是完整运行的代码，主要是将这些数据分成两类，这是我看书自己写的，不知道有什么问题，请求高手相助，bp神经网络以前也没学过，是自己看了一些书，可能还有些地方没弄明白，所以我犯的错误可能在高手眼里不值一提，也有可能让大家觉得很可笑，但不管怎么样程序有哪里不对希望大家能帮我改正，非常感谢！

p=[ 19.5  18.7  13.18 23.72 12.56 12.73 20.32 24.64 12.88 30.58 16.18 25.16 18.14 16.75 13.8  18.95 22.22 26.02 12.86

16.5  17.89 20.35 26.4  14.2  13.54 25.36 30.12 21.01 17.32 19.86 12.55 13.73 22.32 24.78 12.65 32.58 17.18 25.42

20.14 19.75 13.89 20.95 22.23 26.51 13.86 16.52 18.89 20.37 26.49 14.28 12.54 25.33 30.21 21.09 17.41 17.86 18.74

13.19 24.72 13.56 12.74 20.35 23.64 12.88 30.54 17.18 25.14 19.14 18.75 20.13 19.01 15.36 17.45 18.47 20.35 28.43

20.05 21.03 15.31 19.34 18.77 15.62 17.35 12.31 19.58 17.36 20.35 22.34 29.56 24.33 22.06 29.34 25.06 20.45 18.23

6.9   9.01  8.52 10.12 11.17  9.52 10.04  9.36  8.74  9.56 10.01 11.5   9.5   8.85  9.62  7.55  7.98 10.14  9.13

9.56  9.87 11.21  9.63  9.5   9.12  8.89 11.23  9.78  7.54  9.36  8.9   9.91  6.64  8.09  8.89  9.08  8.91 10.01

9.15 10.21 10.17  9.55 10.03  9.46  8.74  6.56 10.23 11.05  8.5   9.85  9.63  7.58  6.98  8.19  9.23  9.59  7.87

11.22  9.64  9.53  9.18  6.89 11.27  8.78  8.54  9.39 10.9   8.91  6.64  8.78  7.98  10.01 6.91 10.23  9.19 10.14

11.16  8.52 10.05  9.37  9.75  9.46 10.03 11.51  9.51  8.98  9.64  8.55  7.97  8.16  9.15  9.46   9.81 10.21 9.62

0.0046  0.0043  0.0044  0.0088  0.0046  0.0043  0.0060  0.0079  0.0043  0.0029  0.0043  0.0061  0.0099  0.0102  0.0034  0.0049  0.0062  0.0052  0.0040

0.0080  0.0073  0.0039  0.0039  0.0050  0.0053  0.0039  0.0069  0.0094  0.0057  0.0046  0.0029  0.0099  0.0046  0.0056  0.0052  0.0083  0.0053  0.0069

0.0053  0.0052  0.0049  0.0066  0.0092  0.0067  0.0038  0.0058  0.0078  0.0102  0.0082  0.0059  0.0049  0.0053  0.0064  0.0089  0.0076  0.0042  0.0061

0.0078  0.0048  0.0039  0.0044  0.0062  0.0097  0.0104  0.0074  0.0058  0.0063  0.0051  0.0048  0.0081  0.0072  0.0043  0.0034  0.0051  0.0054  0.0042

0.0068  0.0095  0.0056  0.0068  0.0031  0.0096  0.0043  0.0059  0.0051  0.0084  0.0043  0.0056  0.0042  0.0062  0.0031  0.0056  0.0039  0.0089  0.005

0.0029  0.0031  0.0042  0.0031  0.0031  0.0033  0.0034  0.0031  0.003   0.004   0.003   0.0028  0.0031  0.0032  0.0038  0.0034  0.0042  0.0035  0.0034

0.0029  0.0041  0.0032  0.0032  0.0037  0.0039  0.0027  0.0031  0.0033  0.0032  0.0041  0.0027  0.0037  0.0033  0.0035  0.0031  0.0034  0.0027  0.0035

0.0027  0.0034  0.0039  0.0037  0.0031  0.0029  0.0031  0.0039  0.0031  0.0023  0.0029  0.0035  0.0039  0.0032  0.0041  0.0038  0.0035  0.0023  0.0036

0.0034  0.0037  0.0041  0.0038  0.0029  0.0041  0.0033  0.0048  0.0034  0.0042  0.0034  0.0024  0.0036  0.0042  0.0031  0.0022  0.0028  0.0031  0.0032

0.0029  0.0034  0.0038  0.0031  0.0024  0.0038  0.0032  0.0036  0.0041  0.0039  0.0028  0.0037  0.0038  0.0031  0.0028  0.0035  0.0028  0.0034  0.0038]';

>> t=[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]';

>> [pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);

>> net=newff(minmax(pn),[5,1],{'tansig','purelin'},'trainlm');

>> net.trainparam.epochs=100;

>> net.trainparam.lr=0.05;

>> net.trainparam.show=50;

>> net.trainparam.goal=0.001;

>> net=train(net,pn,tn);