A Parallel Algorithm for Solving the Toeplitz Least Squares Problem
VECPAR '00 Selected Papers and Invited Talks from the 4th International Conference on Vector and Parallel Processing
On the Stability of the Generalized Schur Algorithm
NAA '00 Revised Papers from the Second International Conference on Numerical Analysis and Its Applications
An Efficient Parallel Algorithm to Solve Block-Toeplitz Systems
The Journal of Supercomputing
Adaptive zero-padding OFDM over frequency-selective multipath channels
EURASIP Journal on Applied Signal Processing
A structured rank-revealing method for Sylvester matrix
Journal of Computational and Applied Mathematics
On the computation of the rank of block bidiagonal Toeplitz matrices
Journal of Computational and Applied Mathematics
Computing multivariate approximate GCD based on Barnett's theorem
Proceedings of the 2009 conference on Symbolic numeric computation
A complete modular resultant algorithm targeted for realization on graphics hardware
Proceedings of the 4th International Workshop on Parallel and Symbolic Computation
An efficient and stable parallel solution for non-symmetric toeplitz linear systems
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
Modular resultant algorithm for graphics processors
ICA3PP'10 Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Proceedings of the 2011 International Workshop on Symbolic-Numeric Computation
Computing resultants on Graphics Processing Units: Towards GPU-accelerated computer algebra
Journal of Parallel and Distributed Computing
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We derive a stable and fast solver for nonsymmetric linear systems of equations with shift structured coefficient matrices (e.g., Toeplitz, quasi-Toeplitz, and product of two Toeplitz matrices). The algorithm is based on a modified fast QR factorization of the coefficient matrix and relies on a stabilized version of the generalized Schur algorithm for matrices with displacement structure. All computations can be done in O(n2) operations, where n is the matrix dimension, and the algorithm is backward stable.