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45 lines
1.5 KiB
Matlab
45 lines
1.5 KiB
Matlab
function pcbc_prob_2integrate_segregate()
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%Perform optimal feature integration given two Gaussian probability distributions. Gradually change the degree of cue conflict to test when integration chnages to segregation.
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stdInputs=20; %30
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stdWeights=15;
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inputs=[-180:10:180];
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centres=[-180:15:180];
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%define weights, to produce a 2d basis function network, where nodes have gaussian RFs.
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W=[];
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for c=centres
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W=[W;code(c,inputs,stdWeights,0,1),code(c,inputs,stdWeights,0,1)];
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end
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W=W./2;
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[n,m]=size(W);
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%define test cases
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stdx=20;
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X=zeros(m,5);
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k=0;
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for m2=-10:20:70
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k=k+1;
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X(:,k)=[code(-20,inputs,stdInputs,0,0,stdx),code(m2,inputs,stdInputs,0,0,stdx)]';
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end
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%present test cases to network and record results
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figure(size(X,2)+1),clf %figure for summary results
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for k=1:size(X,2)
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x=X(:,k);
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[y,e,r]=dim_activation(W,x);
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figure(size(X,2)+1),axes('Position',[0.16*k-0.04,0.15,0.145,0.7]),
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rA=r(1:length(inputs));
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bar(rA.^2,1,'FaceColor',[0,0.7,0]),axis([0.5,length(rA)+0.5,0,0.9])
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if k>1, set(gca,'YTick',[]); end
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set(gca,'XTick',[10:9:length(rA)-1],'XTickLabel',inputs(10:9:length(rA)-1),'FontSize',9);
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text(0.02,0.94,'r_a^2','Units','normalized','color',[0,0.7,0],'FontSize',9,'FontWeight','bold','VerticalAlignment','top')
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hold on, plot(x(1:length(inputs))'.*x(1+length(inputs):end)','LineWidth',2);
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figure(k),clf
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plot_result2(x,r,y,2,inputs,centres);
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end
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figure(size(X,2)+1)
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set(gcf,'PaperSize',[20 3],'PaperPosition',[0 0.25 20 3],'PaperOrientation','Portrait');
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print(gcf, '-dpdf', ['probability_2integrate_segregate_summary.pdf']);
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