I am looking for a fast Eigenvalue and SVD solver for small dense structured matrices (Hankel and Toeplitz). I have searched for efficient implementations in libraries like MKL but I am not able to find anything specific to structured matrices. I found a set of interesting papers on the subject: Luk and Qiao, A Fast Eigenvalue algorithm for Hankel matrices which uses Lancoz tridiagonalization based on FFT and a QR like diagonalization of the tridiagonal matrix for computing eigenvalues with a complexity of $O(n^2\log(n))$.Luk and Qiao, A fast symmetric SVD algorithm for square Hankel matricesDo any of the libraries out there or any implementation you know of use this as I would like to reuse as much as possible? Are there any algorithms which achieve bounds better than this for structured matrices?
Fast Eigenvalue and SVD Solver for Structured Matrices
linear algebra;eigenvalues;svd