Abstract
| Language | English |
|---|---|
| Pages | 1-5 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 11 Sep 2015 |
| Event | 5th Conference of the Sensor Signal Processing for Defence - Royal College of Physicians of Edinburgh, Edinburgh, United Kingdom Duration: 9 Jul 2015 → 10 Jul 2015 http://www.sspd.eng.ed.ac.uk/conference-archive/2015 |
Conference
| Conference | 5th Conference of the Sensor Signal Processing for Defence |
|---|---|
| Abbreviated title | SSPD 2015 |
| Country | United Kingdom |
| City | Edinburgh |
| Period | 9/07/15 → 10/07/15 |
| Internet address |
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Keywords
- sequential matrix diagonalisation algorithms
- polynomial eigenvalue decomposition
- broadband array processing
Cite this
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Shortening of paraunitary matrices obtained by polynomial eigenvalue decomposition algorithms. / Corr, Jamie; Thompson, Keith; Weiss, Stephan; Proudler, Ian K.; McWhirter, John G. .
2015. 1-5 Paper presented at 5th Conference of the Sensor Signal Processing for Defence , Edinburgh, United Kingdom.Research output: Contribution to conference › Paper
TY - CONF
T1 - Shortening of paraunitary matrices obtained by polynomial eigenvalue decomposition algorithms
AU - Corr, Jamie
AU - Thompson, Keith
AU - Weiss, Stephan
AU - Proudler, Ian K.
AU - McWhirter, John G.
N1 - (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.
PY - 2015/9/11
Y1 - 2015/9/11
N2 - This paper extends the analysis of the recently introduced row-shift corrected truncation method for paraunitary matrices to those produced by the state-of-the-art sequential matrix diagonalisation (SMD) family of polynomial eigenvalue decomposition (PEVD) algorithms. The row-shift corrected truncation method utilises the ambiguity in the paraunitary matrices to reduce their order. The results presented in this paper compare the effect a simple change in PEVD method can have on the performance of the paraunitary truncation. In the case of the SMD algorithm the benefits of the new approach are reduced compared to what has been seen before however there is still a reduction in both reconstruction error and paraunitary matrix order.
AB - This paper extends the analysis of the recently introduced row-shift corrected truncation method for paraunitary matrices to those produced by the state-of-the-art sequential matrix diagonalisation (SMD) family of polynomial eigenvalue decomposition (PEVD) algorithms. The row-shift corrected truncation method utilises the ambiguity in the paraunitary matrices to reduce their order. The results presented in this paper compare the effect a simple change in PEVD method can have on the performance of the paraunitary truncation. In the case of the SMD algorithm the benefits of the new approach are reduced compared to what has been seen before however there is still a reduction in both reconstruction error and paraunitary matrix order.
KW - sequential matrix diagonalisation algorithms
KW - polynomial eigenvalue decomposition
KW - broadband array processing
UR - http://www.see.ed.ac.uk/drupal/udrc/sspd/
UR - http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7287474
U2 - 10.1109/SSPD.2015.7288523
DO - 10.1109/SSPD.2015.7288523
M3 - Paper
SP - 1
EP - 5
ER -