Evaluating svd() on slice of matrix array.
1 次查看(过去 30 天)
显示 更早的评论
I have an array of matrices such that
size(A) == [3, 3, 1e3]
for example. These 1000 [3x3] matrices must be orthonormal so I am attempting to project each one to the nearest orthonormal basis, using svd() and the approximation
This function is made to work on a single [3x3] matrix at a time however. A workaround could be using for loops like
[~,~,np] = size(A);
for i=1:np
[U,~,V] = svd(A(:,:,i));
A(:,:,i) = U*V';
end
but this function will be called very often with high numbers of matrices so I am attempting to make efficient. Is there a better way to do this?
0 个评论
回答(1 个)
David Goodmanson
2020-1-23
编辑:David Goodmanson
2020-1-23
Hi Morten
I take it that your matrices are close to being orthonomal already. Try
[Q, ~] = qr(A(:,:,i));
A(:,:,i) = Q;
which is about three times faster, not counting overhead to read and write to A(:,:,i). The result is slightly different, but of course still orthogonal.
0 个评论
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Logical 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!