I have problems in understanding why author of this article uses smallest eigenvalue of a cross product matrix instead of a data matrix. I know that $SVD(AA^T)=UD^2U^T$, but I don't know why not compute $SVD(A)=UDV^T$ and square the smallest value $\lambda_{min}$. Due to measurement and computation inaccuracies, the smallest eigenvalue is then minimized (preferably to $0$).
2026-03-27 21:17:54.1774646274
Reasons of computing smallest eigenvalue $R^TR$ instead of singular value
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