MATLAB: Getting error “Subscript indices must either be real positive integers or logical’

# vector normalization

I am getting this error when I run the following commands. Help needed at the earliest.

v=[1 -2 3];
n=norm(v);

Best Answer

See https://www.mathworks.com/matlabcentral/answers/437735-how-to-replace-nan-values-with-zero#answer_354471

It might happen that you have a variable called norm so try the below:

clear all
% or

clear norm
% or
clear norm global
v=[1 -2 3];
n=norm(v);

Also

which norm -all % what shows up

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MATLAB: Principle Component Analysis (PCA) bi-plot vector magnitude

I am not sure how princomp works, but here is a quick way to do this.

1) mean center your data, meaning subtract the mean across all data points across each dimension from each dimension.

2) [U,S,V]=svd(Data,0);

3) Assuming your dimensions are across columns (meaning your data point are row vectors), PCA weights are U*S, your variance vector is diag(S^2), your PCA vectors are S*V'.

Your results wont be normalized in any way, but they will be centered, and that is desirable in most cases.

MATLAB: Pca() returns 1 less principal component

See you need not to use inbuilt function for pca. Pca is straight forward with few steps. Check the below pca code with out using inbuilt pca function.

a = diag([1 2 3]);
% disp(pca(a));
A = cov(a) ;   % co-variance matrix 
[V,D] = eig(A) ;  % GEt Eigenvalues and Eigenvectors 
Eig = diag(D) ;
[val,idx] = sort(Eig,'descend') ;
PV = Eig(idx)
PC = V(:,idx)
disp(pca(a))

As you see one of the principal values (Eigenvalues) is zero. So pca is not displaying it.

Best Answer

Related Solutions

MATLAB: Principle Component Analysis (PCA) bi-plot vector magnitude

MATLAB: Pca() returns 1 less principal component

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