BP神经网络的trainbr算法，训练后为什么只有一条performance曲线

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。

遇到同样的问题，但是我的函数是newff，该怎么解决呢？