Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
We derive a look-ahead recursive algorithm for the block triangular factorization of Toeplitz-like matrices. The derivation is based on combining the block Schur/Gauss reduction procedure with displacement structure and leads to an efficient block-Schur complementation algorithm. For an Toeplitz-like matrix, the overall computational complexity of the algorithm is operations, where r is the matrix displacement rank and t is the number of diagonal blocks. These blocks can be of any desirable size. They may, for example, correspond to the smallest nonsingular leading submatrices or, alternatively, to numerically well-conditioned blocks.
Daniel Kressner, Zvonimir Bujanovic
Giovanni De Micheli, Massimiliano Di Ventra
Giovanni De Micheli, Heinz Riener, Siang-Yun Lee