How to write my own neural network transfer function which gives discrete outputs 1,2,3.

Question

sri 2013-9-17

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/87395-how-to-write-my-own-neural-network-transfer-function-which-gives-discrete-outputs-1-2-3

I need to get output of a single neuron either 1 or 2 or 3. That is output of a neuron is not just a single value it should multiple values (1,2,3). Please give me an idea about the structure of the neural network..

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Greg Heath 2013-9-18

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/87395-how-to-write-my-own-neural-network-transfer-function-which-gives-discrete-outputs-1-2-3#answer_97178

Not enough info.

Why do you need to do this?

Are inputs discrete or conntinuous?

If the former, you might be able to use hardlim.

If the latter, you will need 2 neurons.

What do you mean by network ... the 2-neuron configuration?

Hope this helps.

Thank you for formally accepting my answer.

Greg

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

sri 2013-9-19

Thanks for replying.

My inputs are continues.

I have 64 inputs and 10 outputs. Each output can have the value 1,2,3 discrete values. So that my network architecture is (64,number of neurons at hidden layer,10).

Since hardlim gives output 0 or -1 I can't apply that for my problem.

请先登录，再进行评论。

Answer 2

Greg Heath 2013-9-19

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/87395-how-to-write-my-own-neural-network-transfer-function-which-gives-discrete-outputs-1-2-3#answer_97236

在 MATLAB Online 中打开

You don't need anything special. Just use fitnet with targets of 1,2,3. You will end up with a continuum of outputs. For example, if the first 5 outputs are

>> y1 = 0.5 + 2.99*rand(10,5)

y1 =

9842    0.6613    2.8749    0.7506    3.3761
2499    2.0871    1.4305    1.1846    0.5139
1437    2.8297    2.0803    3.2309    2.8170
2424    3.2927    0.9953    0.9556    2.9437
3547    0.8884    2.2999    2.9692    3.0974
7640    2.2008    1.2863    2.1096    0.7525
7536    1.9035    2.4557    3.4784    1.6954
6375    0.5356    2.5608    0.7337    1.2770
1978    1.5080    2.7370    1.8236    2.8922
7268    0.9849    1.8471    0.8189    1.7899

>> y = round(y1)

y =

   1     3     1     3
   2     1     1     1
   3     2     3     3
   3     1     1     3
   1     2     3     3
   2     1     2     1
   2     2     3     2
   1     3     1     1
   2     3     2     3
   1     2     1     2