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Abstract
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.
Original language | English |
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Pages | 1-5 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 11 Sept 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 |
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Abbreviated title | SSPD 2015 |
Country/Territory | United Kingdom |
City | Edinburgh |
Period | 9/07/15 → 10/07/15 |
Internet address |
Keywords
- sequential matrix diagonalisation algorithms
- polynomial eigenvalue decomposition
- broadband array processing
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Dive into the research topics of 'Shortening of paraunitary matrices obtained by polynomial eigenvalue decomposition algorithms'. Together they form a unique fingerprint.Projects
- 1 Finished
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Signal Processing Solutions for the Networked Battlespace
Soraghan, J. (Principal Investigator) & Weiss, S. (Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/04/13 → 31/03/18
Project: Research