DocumentCode :
1790815
Title :
Multiple shift maximum element sequential matrix diagonalisation for parahermitian matrices
Author :
Corr, Jamie ; Thompson, Keith ; Weiss, Steven ; McWhirter, John G. ; Redif, Soydan ; Proudler, Ian K.
Author_Institution :
Dept. of Electron. & Electr. Eng., Univ. of Strathclyde, Glasgow, UK
fYear :
2014
fDate :
June 29 2014-July 2 2014
Firstpage :
312
Lastpage :
315
Abstract :
A polynomial eigenvalue decomposition of paraher-mitian matrices can be calculated approximately using iterative approaches such as the sequential matrix diagonalisation (SMD) algorithm. In this paper, we present an improved SMD algorithm which, compared to existing SMD approaches, eliminates more off-diagonal energy per step. This leads to faster convergence while incurring only a marginal increase in complexity. We motivate the approach, prove its convergence, and demonstrate some results that underline the algorithm´s performance.
Keywords :
convergence of numerical methods; eigenvalues and eigenfunctions; iterative methods; matrix decomposition; polynomial matrices; Parahermitian polynomial matrices; SMD algorithm; convergence; iterative approaches; multiple shift maximum element sequential matrix diagonalisation; off-diagonal energy per step; polynomial eigenvalue decomposition; Approximation algorithms; Convergence; Educational institutions; Jacobian matrices; Matrix decomposition; Polynomials; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing (SSP), 2014 IEEE Workshop on
Conference_Location :
Gold Coast, VIC
Type :
conf
DOI :
10.1109/SSP.2014.6884638
Filename :
6884638
Link To Document :
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