rotate singular values from svd in matlab

You can rotate singular values obtained from Singular Value Decomposition (SVD) in MATLAB by performing transformations on the original matrices. Here's an example demonstrating how to rotate singular values:

main.m
% Perform Singular Value Decomposition
A = rand(5, 3);  % Example matrix
[U, S, V] = svd(A);

% Rotate singular values by adding a rotation matrix
theta = pi/4; % Rotation angle
R = [cos(theta) -sin(theta); sin(theta) cos(theta)]; % Rotation matrix

S_rotated = S(1:2, 1:2) * R; % Rotate the top 2x2 singular values

% Reconstruct the original matrix with rotated singular values
A_rotated = U(:,1:2) * S_rotated * V(:,1:2)';

disp(A_rotated);
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In this example, we first perform SVD on a random matrix A. Then, we specify a rotation angle and create a 2x2 rotation matrix R. Next, we rotate the top 2x2 singular values using the rotation matrix R. Finally, we reconstruct the original matrix with the rotated singular values.

Please note that rotating singular values may not always produce meaningful results depending on the application.