Eigendecomposition, Singular-Values and the Power Method
Description
For a data matrix with m rows and n columns (m>=n), the power
method is used to compute, simultaneously, the eigendecomposition
of a square symmetric matrix. This result is used to obtain the
singular value decomposition (SVD) and the principal component
analysis (PCA) results. Compared to the classical SVD method,
the first r singular values can be computed.