matlab BP神经网络训练程序求解释

楼主解决没？这是我知道的

[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t)%归一化数据，方便后面的预测

net.trainParam. show = 100 %这里的show是显示步数，每100步显示一次

net.trainParam.goal=0.0001%目标误差，训练得到的数据和原始输入

net.trainParam.lr = 0.01 %lr是学习动量，一般越小越好

y1=sim(net,pn) %sim用来预测的

xlswrite('testdata6',tnew1) ？这里的testdata6是excel表格的名称

你可以看看书的，书上都有介绍

trainbr算法用的较少。一般在divide up samples 前， 把normInput, 和 normTarget 留下一部分作为validation。

阅读下trainbr函数的帮助：

net.trainParam.max_fail 5 Maximum validation failures

If VV is not [], it must be a

structure of validation vectors,

VV.PD - Validation delayed inputs.

VV.Tl - Validation layer targets.

VV.Ai - Validation initial input conditions.

VV.Q - Validation batch size.

VV.TS - Validation time steps.

which is normally used to stop training early if the

network performance on the validation vectors fails to improve or remains the

same for max_fail epochs in a row.

If TV is not [], it must be a structure of

validation vectors,

TV.PD - Validation delayed inputs.

TV.Tl - Validation layer targets.

TV.Ai - Validation initial input conditions.

TV.Q - Validation batch size.

TV.TS - Validation time steps.

which is used to test the generalization capability of the trained network.

说明还是有划分样本的，仔细研究下吧。

---