Question: LS, SVD and Orthogonal Matrix

This question is related to the Question right-angled triangle

How can I show that the Least Square solution x = (A'.A)^-1.A'.y
Is different when A is an orthogonal matrix compared to an
overdetermined or underdetermind matrix.

Preferably transform the matrix using Singular Value Decomposition (SVD)
or something similar.


Please Wait...