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Matlab

function [W,V,U]=weight_initialisation_random(n,m,wMean,wStd)
if nargin<3, wMean=0.5; end
if nargin<4, wStd=0.05; end
W=gaussian_weights(n,m,wMean,wStd);
V=gaussian_weights(n,m,wMean,wStd);
U=gaussian_weights(n,m,wMean,wStd);
function W=gaussian_weights(n,m,wMean,wStd)
W=wMean+wStd.*randn(n,m,'single'); %Gaussian distributed weights with given
W(find(W<0))=0; %mean and standard deviation