# How can I adapt this script (to test the robustness of a perceptron) to test the robustness of a multi-layer perceptron?

The following script is from Trappenberg's Fundamentals of Computational Neuroscience and is used to test a perceptron's robustness against noise.

However, how would one alter it to test the output of a multilayer perceptron?

In particular, wOut and rIn are non-conformable because the wOut of a multilayer perceptron with 2 hidden layers is $$26*2$$.

So, how could I alter this to test the trained multilayer perceptron?

%% Testing generalization perfroamnce of trained perceptron
perceptron_network_sim;
letterMatrix=rIn;
for nflip = 1:80;
dist1=[]; dist2=[];
for trial=1:10;
rIn=abs(letterMatrix-randomFlipMatrix(nflip));
% Threshold output function
rOut1=(wOut*rIn)>0;
nerror=0;
for j=1:26; nerror=nerror+(sum(rDes(:,j)~=rOut1(:,j))>0); end
dist1=[dist1,nerror];
% Max output function
[v,i]=max(wOut*rIn);
rOut2=zeros(26); for j=1:26; rOut2(i(j),j)=1; end
dist2=[dist2,0.5*sum(sum(rDes~=rOut2))];
end
meanDist1(nflip)=mean(dist1); stdDist1(nflip)=std(dist1);
meanDist2(nflip)=mean(dist2); stdDist2(nflip)=std(dist2);
end
figure; hold on;
errorbar((1:80)/156,meanDist1,stdDist1,':')
errorbar((1:80)/156,meanDist2,stdDist2,'r')
xlabel('Fraction of flipped bits')
ylabel('Average number of wrong letters')

• Hi and welcome to AI SE! What programming language is this? Matlab? – nbro Apr 7 '20 at 16:29
• Thank you. Yes this is Matlab. – syntheso Apr 7 '20 at 17:29