神经网络不训练

Question

我正在尝试建立一个自定义神经网络，但是当我训练它时，它不会训练：训练过程进行0次迭代！我没有得到任何错误，只有0次迭代，我不知道为什么。 （这个架构对你来说可能很奇怪，它应该是一个自定义的PNN。但在我们讨论它是否有意义之前，我希望能够训练它......）

这是代码

  net = network;
  net.trainFcn = 'trainlm';
  net.performFcn = 'mse';
  net.numInputs = 1;
  net.numLayers = (2*nbclasses)+1; % (one pattern layer + one summation layer per class) + competition layer
  net.inputConnect(1:nbclasses,:) = 1; % connects the input to all pattern layers

    for i = 1:nbclasses % Connect the pattern layers to their corresponding summation layers
        net.layerConnect(i+nbclasses,i) = 1;
        net.layers{i}.size = size(tr_feature,1);
        net.layers{i}.transferFcn = 'radbas';
    end

    for i = (nbclasses+1):(nbclasses*2) % Connect all summation layers to the competition layer
        net.layers{i}.size = 1;
        net.layerConnect(net.numLayers,i) = 1;
    end

    net.layers{net.numLayers}.transferFcn = 'compet';    
    net.outputConnect(1,end) = 1;
    net.view;
    [net, tr] = train(net,tr_feature',tr_true');
    % tr_feature is a 800x2 data matrix, tr_true is the 800x1 corresponding labels

有什么想法吗？

提前致谢！