Shortening of paraunitary matrices obtained by polynomial eigenvalue decomposition algorithms

Jamie Corr; Keith Thompson; Stephan Weiss; Ian K. Proudler; John G.  McWhirter

doi:10.1109/SSPD.2015.7288523

Shortening of paraunitary matrices obtained by polynomial eigenvalue decomposition algorithms

Jamie Corr, Keith Thompson, Stephan Weiss, Ian K. Proudler, John G. McWhirter

Electronic And Electrical Engineering

Research output: Contribution to conference › Paper

11 Citations (Scopus)

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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
Pages	1-5
Number of pages	5
DOIs	https://doi.org/10.1109/SSPD.2015.7288523
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	http://www.sspd.eng.ed.ac.uk/conference-archive/2015

Keywords

sequential matrix diagonalisation algorithms
polynomial eigenvalue decomposition
broadband array processing

Access to Document

10.1109/SSPD.2015.7288523

Corr-etal-SSPD-2015-Shortening-of-paraunitary-matrices-obtained-by-polynomialAccepted author manuscript, 247 KB

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Signal Processing Solutions for the Networked Battlespace
Soraghan, J. & Weiss, S.
EPSRC (Engineering and Physical Sciences Research Council)
1/04/13 → 31/03/18
Project: Research

Cite this

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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.",

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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.

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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.

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KW - polynomial eigenvalue decomposition

KW - broadband array processing

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Y2 - 9 July 2015 through 10 July 2015

ER -

Shortening of paraunitary matrices obtained by polynomial eigenvalue decomposition algorithms

Abstract

Conference

Keywords

Access to Document

Signal Processing Solutions for the Networked Battlespace

Cite this