sensitivity analysis, multilayer, feed-forward, back-propagation neural network using MATLAB.

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Majda Eljaat 2014-4-6

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编辑： Andualem alemu 2015-4-7

How can I carry out a sensitivity analysis, that is, the effect of input parameters on the output of a multilayer, feed-forward, back-propagation neural network using MATLAB. What is the code for this, or is there any inbuilt function to carry out ?

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Greg Heath 2014-4-11

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For a simple MIMO MLP, the I/O relationship is

 [ I N ] = size(x);
 [ O N ] = size(y);
 y = b2 + LW*tanh(b1+IW*x);
 Just take gradients with respect to whatever parameter component you are interested in.

Hope this helps.

Thank you for formally accepting my answer

Greg

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Greg Heath 2015-4-7

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I am confused. Yesterday you wrote

" this makes it clear. thank you"

but today you wrote

"...are not clear."

What has changed? More to the point: Did you learn anything at all from the formula? If so, what?

The following should help:

 h = tansig( b1 + IW*x ); % HIDDEN LAYER
 y = b2 + LW*h;           % OUTPUT LAYER

Andualem alemu 2015-4-7

编辑：Andualem alemu 2015-4-7

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I am sorry that I am bothering you too much. But it is because I am absolute beginner and so curious to know, work on and understand MLP and ensemble MLP for time series forecasting!!

Dear sir my question is in the formula:

y = b2 + LW*tanh(b1+IW*x);

What is Y, b2, LW, b1, IW and x ?

what are they representing and how can I find their value?

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