Abstract Let A be an n × n Hermitian matrix and A = UΛUH be its spectral decomposition, where U is a unitary matrix of order n and Λ is a diagonal matrix. In this note we present the perturbation ...

However, it's possible to compute eigenvalues and eigenvectors indirectly using singular value decomposition (SVD). If you have a matrix A and apply singular value decomposition, the three results are ...

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...