Thanks! One reference for tracking eigenvalues with Jacobi is http://www.sciencedirect.com/science/article/pii/S002437950000046X Proper implementation of Jacobi requires blocking and some preconditioning (see LAPACK's dgesvj.f). I will take your suggestion seriuosly and see what to do about implementing Jacobi EVD and SVD in Julia.
Dana utorak, 21. lipnja 2016. u 14:46:58 UTC+2, korisnik Dawid Crivelli napisao je: > Thanks for the notes, they look interesting. > > The Jacobi algorithm coded in Julia by someone competent is also very > welcome - I heard it's perfect for tracking the evolution of eigenvalues > when a matrix is continuously transformed, but I was too lazy to implement > it myself! Probably a dedicated package might be useful to more people. > > >> The lecture notes are all Jupyter notebooks, see >> https://github.com/ivanslapnicar/GIAN-Applied-NLA-Course >> >> Any feedback is welcome! >> >
