MATLAB normalize train and test

matrixTrain = load('matrix.train');

 function [matrixTrain , meanFeatIn, stdDevFeatIn] = mynorm_train(matrixTrain)

featureIn = matrixTrain(:,1:end-1);
featureOut = matrixTrain(:,end);

meanFeatIn = mean(featureIn,1);
stdDevFeatIn = std(featureIn,1,1);
meanFeatOut = mean(featureOut,1);
stdDevFeatOut = std(featureOut,1,1) ; 
dlmwrite('normInfo',[meanFeatOut stdDevFeatOut],'delimiter','\t');
noSample = size(featureIn,1);
 for i=1:noSample
            featureIn(i,:) = (featureIn(i,:) - meanFeatIn) ./ stdDevFeatIn ;
            featureOut(i,:) = (featureOut(i,:) - meanFeatOut) ./ stdDevFeatOut ;
 end
matrixTrain = [ featureIn featureOut];

end

matrixTest = load('matrix.test');

function [matrixTest] = mynorm_train(matrixTest,meanFeatIn, stdDevFeatIn,meanFeatOut ,stdDevFeatOut )

noSample = size(matrixTest,1);
noInputFeat = size(matrixTest,2) - 1;
for i=1:noSample
            matrixTest(i,1:noInputFeat) = (matrixTest(i,1:noInputFeat) - meanFeatIn )  ./ stdDevFeatIn ;
            matrixTest(i,noInputFeat+1) = (matrixTest(i,noInputFeat+1) - meanFeatOut )  ./ stdDevFeatOut ;  
end