algorithm - matlab中时滞神经网络的反向传播算法

Question

我在 matlab 中使用时间延迟神经网络，我想用不同的训练算法训练它。我使用了很多这些算法，例如粒子群优化、levenberg marquardt、准牛顿和...。现在我想使用反向传播，但我不能使用 traingd 函数，因为时间延迟神经网络的反向传播不同于前馈 betwork。任何人都可以告诉我 matlab 中是否有任何函数用于训练 TDNN 是否具有反向传播？

谢谢

Answer 1

来自 mathworks :

One nice feature of the FTDNN is that it does not require dynamic backpropagation to compute the network gradient. This is because the tapped delay line appears only at the input of the network, and contains no feedback loops or adjustable parameters. For this reason, you will find that this network trains faster than other dynamic networks.

使用timedelaynet(inputDelays,hiddenSizes,trainFcn)

Example :

[X,T] = simpleseries_dataset;
net = timedelaynet(1:2,10)
[Xs,Xi,Ai,Ts] = preparets(net,X,T)
net = train(net,Xs,Ts,Xi,Ai);
view(net)
Y = net(Xs,Xi,Ai);
perf = perform(net,Ts,Y)