### Abstract

Language | English |
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Title of host publication | 2007 6th International conference on information, communications & signal processing |

Place of Publication | New York |

Publisher | IEEE |

Pages | 1396-1400 |

Number of pages | 5 |

ISBN (Print) | 9781424409822 |

DOIs | |

Publication status | Published - 2007 |

Event | 6th Conference on Information, Communications, and Signal Processing - , Singapore Duration: 10 Dec 2007 → 13 Dec 2007 |

### Conference

Conference | 6th Conference on Information, Communications, and Signal Processing |
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Country | Singapore |

Period | 10/12/07 → 13/12/07 |

### Fingerprint

### Keywords

- hermitian matrices
- polynomial matrices
- eigenvalues
- eigenfunctions
- paraunitary matrices
- SBR2 algorithm

### Cite this

*2007 6th International conference on information, communications & signal processing*(pp. 1396-1400 ). New York: IEEE. https://doi.org/10.1109/ICICS.2007.4449828

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*2007 6th International conference on information, communications & signal processing.*IEEE, New York, pp. 1396-1400 , 6th Conference on Information, Communications, and Signal Processing, Singapore, 10/12/07. https://doi.org/10.1109/ICICS.2007.4449828

**Shortening the order of paraunitary matrices in SBR2 algorithm.** / Ta, C.H.; Weiss, S.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

TY - GEN

T1 - Shortening the order of paraunitary matrices in SBR2 algorithm

AU - Ta, C.H.

AU - Weiss, S.

PY - 2007

Y1 - 2007

N2 - The second order sequential best rotation (SBR2) algorithm has recently been proposed as a very effective tool in decomposing a para-Hermitian polynomial matrix R(z) into a diagonal polynomial matrix T(z) and a paraunitary matrix B(,z), extending the eigenvalue decomposition to polynomial matrices, R-(z) = B(z)T(z)~B(z). However, the algorithm results in polynomials of very high order, which limits its applicability. Therefore, in this paper we evaluate approaches to reduce the order of the paraunitary matrices, either within each step of SBR2, or after convergence. The paraunitary matrix B(z) is replaced by a near-paraunitary quantity BN(z), whose error will be assessed. Simulation results show that the proposed truncation can greatly reduce the polynomial order while retaining good near-paraunitariness of BN(z).

AB - The second order sequential best rotation (SBR2) algorithm has recently been proposed as a very effective tool in decomposing a para-Hermitian polynomial matrix R(z) into a diagonal polynomial matrix T(z) and a paraunitary matrix B(,z), extending the eigenvalue decomposition to polynomial matrices, R-(z) = B(z)T(z)~B(z). However, the algorithm results in polynomials of very high order, which limits its applicability. Therefore, in this paper we evaluate approaches to reduce the order of the paraunitary matrices, either within each step of SBR2, or after convergence. The paraunitary matrix B(z) is replaced by a near-paraunitary quantity BN(z), whose error will be assessed. Simulation results show that the proposed truncation can greatly reduce the polynomial order while retaining good near-paraunitariness of BN(z).

KW - hermitian matrices

KW - polynomial matrices

KW - eigenvalues

KW - eigenfunctions

KW - paraunitary matrices

KW - SBR2 algorithm

U2 - 10.1109/ICICS.2007.4449828

DO - 10.1109/ICICS.2007.4449828

M3 - Conference contribution book

SN - 9781424409822

SP - 1396

EP - 1400

BT - 2007 6th International conference on information, communications & signal processing

PB - IEEE

CY - New York

ER -