Different kind of normalization
显示 更早的评论
I have read in Matlab that normalization of a vector is u/norm(u).
However, I have a matrix (N x N)where the columns are different vectors. I want for each element of column vectors to do something like: (u(i) - mean(u))/std(u) without looping so that at the end of it each column vectors are bunch of standard normals.
Is there a standard way to do it in matlab or do I really have to code the loop.
采纳的回答
Oleg Komarov
2011-3-15
% Create standard normal distributed samples with std = 100;
A = randn(100000,10)*100;
% Normalize
B = bsxfun(@rdivide,bsxfun(@minus,A,mean(A)), std(A));
% Check first column
hist(B(:,1),100)
Note that mean and std operate along rows, i.e. for a matrix they give a result for each column.
Oleg
更多回答（2 个）
Matt Tearle
2011-3-15
0 个投票
If you have Statistics Toolbox, use uhat = zscore(u).
类别
在 帮助中心 和 File Exchange 中查找有关 Numerical Integration and Differentiation 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Translated by 
