Your code looks fairly good, but there are a few things I would do differently:
It's very confusing that you call
B_repforB, and callBthe mean ofB_rep. The comment and code here looks very strange. You should callB_mean = mean(B_rep, 1)to stick with the general naming convention in your code.B_meanB=bsxfun(@minus,B_rep,B); % B minus mean values of Bbsxfunperforms better thanrepmat, so instead ofB_rep=repmat(matrice2,[1 1 n2]);you can do:B_rep = bsxfun(@times, matrice2, ones(1,1,n2));Instead of
', you should use.'when transposing an array. The first one is the complex conjugated transpose.iandjare bad variable names in Matlabiandjare bad variable names in Matlab.You should try to use more spaces. It makes the code much easier to read.
I don't have the statistical toolbox, so I can't test your code myself. I'm not sure how it can be vectorized, so I can't help with much when it comes performance gain I'm afraid.
Your code looks fairly good, but there are a few things I would do differently:
It's very confusing that you call
B_repforB, and callBthe mean ofB_rep. The comment and code here looks very strange. You should callB_mean = mean(B_rep, 1)to stick with the general naming convention in your code.B_meanB=bsxfun(@minus,B_rep,B); % B minus mean values of Bbsxfunperforms better thanrepmat, so instead ofB_rep=repmat(matrice2,[1 1 n2]);you can do:B_rep = bsxfun(@times, matrice2, ones(1,1,n2));Instead of
', you should use.'when transposing an array. The first one is the complex conjugated transpose.You should try to use more spaces. It makes the code much easier to read.
I don't have the statistical toolbox, so I can't test your code myself. I'm not sure how it can be vectorized, so I can't help with much when it comes performance gain I'm afraid.
Your code looks fairly good, but there are a few things I would do differently:
It's very confusing that you call
B_repforB, and callBthe mean ofB_rep. The comment and code here looks very strange. You should callB_mean = mean(B_rep, 1)to stick with the general naming convention in your code.B_meanB=bsxfun(@minus,B_rep,B); % B minus mean values of Bbsxfunperforms better thanrepmat, so instead ofB_rep=repmat(matrice2,[1 1 n2]);you can do:B_rep = bsxfun(@times, matrice2, ones(1,1,n2));Instead of
', you should use.'when transposing an array. The first one is the complex conjugated transpose.You should try to use more spaces. It makes the code much easier to read.
I don't have the statistical toolbox, so I can't test your code myself. I'm not sure how it can be vectorized, so I can't help with much when it comes performance gain I'm afraid.
Your code looks fairly good, but there are a few things I would do differently:
It's very confusing that you call
B_repforB, and callBthe mean ofB_rep. The comment and code here looks very strange. You should callB_mean = mean(B_rep, 1)to stick with the general naming convention in your code.B_meanB=bsxfun(@minus,B_rep,B); % B minus mean values of Bbsxfunperforms better thanrepmat, so instead ofB_rep=repmat(matrice2,[1 1 n2]);you can do:B_rep = bsxfun(@times, matrice2, ones(1,1,n2));Instead of
', you should use.'when transposing an array. The first one is the complex conjugated transpose.You should try to use more spaces. It makes the code much easier to read.
I don't have the statistical toolbox, so I can't test your code myself. I'm not sure how it can be vectorized, so I can't help with much when it comes performance gain I'm afraid.