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Back Propagation Neural Network

 I need a workable Back Propagation NN code. My Inputs are 100X3 dimension and outputs are 100X2 dimension.Sample size is 100.

For example 1st 5 samples are inputs [-46 -69 -82; -46 -69 -82; -46 -69 -82; -46 -69 -82; -46 -69 -82;... ] and outputs are [0 0;2 1;5 5;4 3; 3 5;...].
Please suggest me if BP is suitable for my problem and what learning technique and activation function will be better to solve this problem? Do I need to apply generalization? Kindly help me with the matlab code if possible. Thank you very much.


ANSWER



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Convert to matrices and transpose
 
 
[I N ] = size(inputs)

 [ O N ] = size(targets)

Use fitnet for regression and curve-fitting

 help fitnet
 doc fitnet
Use patternnet for classification and pattern-recognition
For examples beyond the help/doc documentation try searching with

SEE COMPLETE ANSWER CLICK THE LINK

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