Projects per year
Abstract
This paper introduces a causality constrained sequential matrix diagonalisation (SMD) algorithm, which generates a causal paraunitary transformation that approximately diagonalises and spectrally majorises a parahermitian matrix, and can be used to determine a polynomial eigenvalue decomposition. This algorithm builds on a multiple shift technique which speeds up diagonalisation per iteration step based on a particular search space, which is constrained to permit a maximum number of causal time shifts. The results presented in this paper show the performance in comparison to existing algorithms, in particular an unconstrained multiple shift SMD algorithm, from which our proposed method derives.
Original language  English 

Title of host publication  2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO) 
Publisher  IEEE 
Pages  12771281 
Number of pages  5 
ISBN (Print)  9780992862619 
Publication status  Published  Sep 2014 
Event  22nd European Signal Processing Conference  Lisbon Congress Centre, Lisbon, Portugal Duration: 1 Sep 2014 → 5 Sep 2014 Conference number: 2014 
Conference
Conference  22nd European Signal Processing Conference 

Abbreviated title  EUSIPCO 
Country  Portugal 
City  Lisbon 
Period  1/09/14 → 5/09/14 
Keywords
 eigenvalues and eigenfunctions
 iterative methods
 matrix decomposition
 causal paraunitary transformation
 causal time shifts
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Projects
 1 Finished

Signal Processing Solutions for the Networked Battlespace
EPSRC (Engineering and Physical Sciences Research Council)
1/04/13 → 31/03/18
Project: Research
Activities
 1 Participation in conference

22nd European Signal Processing Conference
Jamie Corr (Participant)
1 Sep 2014 → 5 Sep 2014Activity: Participating in or organising an event types › Participation in conference