An algorithm for calculating the QR and singular value decompositions of polynomial matrices
IEEE Transactions on Signal Processing
Polynomial eigen-beamformer in time domain for MIMO-OFDM systems
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
On Jacobi-type methods for blind equalization of paraunitary channels
Signal Processing
| Hi-index | 35.69 |
An algorithm for computing the eigenvalue decomposition of a para-Hermitian polynomial matrix is described. This amounts to diagonalizing the polynomial matrix by means of a paraunitary "similarity" transformation. The algorithm makes use of "elementary paraunitary transformations" and constitutes a generalization of the classical Jacobi algorithm for conventional Hermitian matrix diagonalization. A proof of convergence is presented. The application to signal processing is highlighted in terms of strong decorrelation and multichannel data compaction. Some simulated results are presented to demonstrate the capability of the algorithm