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A DFT-based approximate eigenvalue and singular value decomposition of polynomial matrices
2013
EURASIP Journal on Advances in Signal Processing
In this article, we address the problem of singular value decomposition of polynomial matrices and eigenvalue decomposition of para-Hermitian matrices. Discrete Fourier transform enables us to propose a new algorithm based on uniform sampling of polynomial matrices in frequency domain. This formulation of polynomial matrix decomposition allows for controlling spectral properties of the decomposition. We set up a nonlinear quadratic minimization for phase alignment of decomposition at each
doi:10.1186/1687-6180-2013-93
fatcat:w3g3lrf2g5hk3aad4dr27qkdze