Abstract
| Language | English |
|---|---|
| Title of host publication | 2016 24th European Signal Processing Conference |
| Place of Publication | Piscataway |
| Publisher | IEEE |
| Pages | 1633-1637 |
| Number of pages | 5 |
| ISBN (Print) | 9780992862657 |
| DOIs | |
| Publication status | Published - 1 Dec 2016 |
| Event | 24th European Signal Processing Conference - Hilton Budapest, Budapest, Hungary Duration: 29 Aug 2016 → 2 Sep 2016 http://www.eusipco2016.org/ |
Publication series
| Name | |
|---|---|
| ISSN (Electronic) | 2076-1465 |
Conference
| Conference | 24th European Signal Processing Conference |
|---|---|
| Abbreviated title | EUSIPCO'16 |
| Country | Hungary |
| City | Budapest |
| Period | 29/08/16 → 2/09/16 |
| Internet address |
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Keywords
- iterative calculation
- polynomial matrices
- polynomial matrix eigenvalue decomposition
- parahermitian matrix
- broadband multichannel problems
- narrowband
- diagonalization
- diagonalisation
Cite this
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Memory and complexity reduction in parahermitian matrix manipulations of PEVD algorithms. / Coutts, Fraser K.; Corr, Jamie; Thompson, Keith; Weiss, Stephan; Proudler, Ian K.; McWhirter, John G. .
2016 24th European Signal Processing Conference. Piscataway : IEEE, 2016. p. 1633-1637.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
TY - GEN
T1 - Memory and complexity reduction in parahermitian matrix manipulations of PEVD algorithms
AU - Coutts, Fraser K.
AU - Corr, Jamie
AU - Thompson, Keith
AU - Weiss, Stephan
AU - Proudler, Ian K.
AU - McWhirter, John G.
N1 - © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is a generalisation of the ordinary EVD and will diagonalise a parahermitian matrix via paraunitary operations. This paper addresses savings — both computationally and in terms of memory use — that exploit the parahermitian structure of the matrix being decomposed, and also suggests an implicit trimming approach to efficiently curb the polynomial order growth usually observed during iterations of the PEVD algorithms. We demonstrate that with the proposed techniques, both storage and computations can be significantly reduced, impacting on a number of broadband multichannel problems.
AB - A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is a generalisation of the ordinary EVD and will diagonalise a parahermitian matrix via paraunitary operations. This paper addresses savings — both computationally and in terms of memory use — that exploit the parahermitian structure of the matrix being decomposed, and also suggests an implicit trimming approach to efficiently curb the polynomial order growth usually observed during iterations of the PEVD algorithms. We demonstrate that with the proposed techniques, both storage and computations can be significantly reduced, impacting on a number of broadband multichannel problems.
KW - iterative calculation
KW - polynomial matrices
KW - polynomial matrix eigenvalue decomposition
KW - parahermitian matrix
KW - broadband multichannel problems
KW - narrowband
KW - diagonalization
KW - diagonalisation
UR - http://ieeexplore.ieee.org/servlet/opac?punumber=1801907
UR - http://www.eusipco2016.org/
U2 - 10.1109/EUSIPCO.2016.7760525
DO - 10.1109/EUSIPCO.2016.7760525
M3 - Conference contribution book
SN - 9780992862657
SP - 1633
EP - 1637
BT - 2016 24th European Signal Processing Conference
PB - IEEE
CY - Piscataway
ER -