25 个向量，3 维输出神经网络
我该如何摆脱错误。 我似乎无法训练我的神经网络以获得 3 维输出。 错误说
???使用 ==> 时出错网络.sim 位于 178 输入的网络大小不正确。 矩阵必须有 1 行。
错误==> 10 点测试
Y = sim(net,P);
addpath('data')
load('ComPoles_Cir_Cy_Rect')
load('target_row')
P = Poles_Circle_10cm;
T = Poles_Rectangular_40cm;
m = min(min(P));
mx = max(max(P));
net = newff([m mx],[10 10 1],{'tansig' 'tansig' 'purelin'});
Y = sim(net,P);
plot(P,T,P,Y,'o')
net.trainParam.epochs = 150;
net = train(net,P,T);
Y = sim(net,P);
plot(P,T,P,Y,'o') `
How do I get rid of the error.
I can't seem to train my neural network for a 3 dimensional output.
The error says
??? Error using ==> network.sim at 178
Inputs are incorrectly sized for network.
Matrix must have 1 rows.
Error in ==> testtt at 10
Y = sim(net,P);
addpath('data')
load('ComPoles_Cir_Cy_Rect')
load('target_row')
P = Poles_Circle_10cm;
T = Poles_Rectangular_40cm;
m = min(min(P));
mx = max(max(P));
net = newff([m mx],[10 10 1],{'tansig' 'tansig' 'purelin'});
Y = sim(net,P);
plot(P,T,P,Y,'o')
net.trainParam.epochs = 150;
net = train(net,P,T);
Y = sim(net,P);
plot(P,T,P,Y,'o') `
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评论（2）
错误消息非常清楚：它期望一个只有一行的矩阵（1xM 矩阵），但它得到了其他东西。
现在，希望这意味着您只需要在代码中转置一些矩阵，它应该可以工作。否则，您可能错误地使用了该函数，并且您需要更多地思考您想要做什么。
The error message is clear enough: It expected a matrix with one row (a 1xM matrix), and it got something else.
Now, hopefully, this means that you only need to transpose some matrix in your code, and it should work. Otherwise, you are probably using the function wrong, and you need to do some more thinking about what you are trying to do.
显然，在没有任何有关 P 和 m 大小的信息的情况下，我可以猜测这种情况下的问题是什么。 MATLAB NN Toolbox 需要输入和输出向量的数据按列排序，这意味着如果您有一个具有 X 个输入的神经网络，则必须使用具有 X 行和 N 列的矩阵，其中 N 是输入样本的数量。输出数据也是如此。这是 NN Toolbox 在学习过程中最常见的错误。
Obviously, without any information about the size of P and m I can guess what is the problem in this case. MATLAB NN Toolbox wants input and output vectors with data ordered in columns, this means that if you have a Neural Network with X inputs, you must use a matrix with X rows and N columns, with N the number of input samples. The same for output data. This is the most common error with NN Toolbox during its learning.