Inputs and number of neuron

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Pawel Osadnik
Pawel Osadnik 2018-6-12
评论： Pawel Osadnik 2018-6-20
Hello, I am preparing a NN for Road Sing Recognicon and it working but not very well. I would like to ask for some advice. I have 954 images of Road Sign, each images has 140x125 = 17500 piksels and my question is, how much i should to have neuron in my network ?
P=cell2mat(struct2cell(all)); %load my pattern
P=reshape(P,17500,954); %matrix with all inputs
% NETWORK
T=eye(3,954); %NETWORK ANSWER
net=newff(P,T,[954],{'hardlims'},'traingd','learngd','mse'); %954 neurons because it is number of my images ?

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Greg Heath
Greg Heath 2018-6-12
I use the concept
Number of training equations Ntrneq >> Number of unknown weights Nw
For a single layer I-H-O net with I-dimensional inputs, O-dimensional outputs and H hidden nodes,
Ntrneq = Ntrn*O % (Typically, Default Ntrn ~ 0.7*N)
Nw = (I+1)*H + (H+1)*O = O + (I+O+1)*H
Ntrn * O >> O + (I+O+1)*H
When Ntrn is too small and/or H is too large, trainlm is usually replaced by trainbr and/or other "overfitting" mitigations are available.
Hope this helps.
Thank you for formally accepting my answer
Greg
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Pawel Osadnik
Pawel Osadnik 2018-6-20
I have one question, you mean Ntrn ~ 0.7*N it's equal 0.7*Numer of neurons ?

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