First Neural Network Using XOR

12 次查看（过去 30 天）
Darryl
Darryl 2013-2-25
I am trying to implement a simple XOR network. All is okay once the input and target data has been setup, but as soon as I try and train the network I get the Neural Network Training Tool window open, but the "stop training" and "cancel" button are shaded out with "minimum gradient reached". As soon as I try and simulate the network, the XOR_NET_output data is wrong and there seems to be error data within the XOR_NET_errors.
I can provide more data if necessary.
  1 个评论
Shashank Prasanna
Shashank Prasanna 2013-2-25
Since this is a fairly simple setup, could you share your data and the lines of code you've written? It will be easier to look into the issue.

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Greg Heath
Greg Heath 2013-2-27
编辑：Greg Heath 2013-2-27
I have many posts on the NEWSGROUP, ANSWERS and comp.ai.neural-nets re XOR. Most can be retreived by searching on
greg xor
The minimal configuration has a 2-2-1 topology with Nw = (2+1)*2+(2+1)*1 = 9 unknown weights to be estimated with only 4 equations. Consequently, there are an infinite number of solutions.
Nevertheless, I recall a success rate of only ~ 70% when training from a random set of initial weights generated by MATLAB's default NW algorithm.
So, just try 10 or more different random weight initializations. You should get at least 5 successful solutions.
Hope this helps.
Thank you for formally accepting my answer.
Greg

更多回答（1 个）

Mohan
Mohan 2013-2-26
The implementation of the XOR with neural networks is clearly explained with Matlab code in "Introduction to Neural Networks Using Matlab 6.0 " by S. N. Sivanandam, S. N Deepa

类别

在 Help Center 和 File Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by