Applications of singular-value decomposition (SVD) (Q1887817)

This work, supported by the Russian Ministry of Education, proposes and illustrates the use of singular-value decomposition (SDV) in terms of \(2\times 2\) matrices, using the suggestive terms ``hanger'', ``aligner'', ``stretcher'' and claiming that the use of SVD in education is still in its infancy. The paper explains the ideas in terms of transformations of conic sections, proceeding numerically, with Mathematica as the software. The last part of the paper applies SVD to linear least squares problems.