Projects per year
Polynomial parahermitian matrices can accurately and elegantly capture the space-time covariance in broadband array problems. To factorise such matrices, a number of polynomial EVD (PEVD) algorithms have been suggested. At every step, these algorithms move various amounts of off-diagonal energy onto the diagonal, to eventually reach an approximate diagonalisation. In practical experiments, we have found that the relative performance of these algorithms depends quite significantly on the type of parahermitian matrix that is to be factorised. This paper aims to explore this performance space, and to provide some insight into the characteristics of PEVD algorithms.
|Publication status||Published - 1 Dec 2015|
|Event||2nd IET International Conference on Intelligent Signal Processing - Kensington Close Hotel, London, United Kingdom|
Duration: 1 Dec 2015 → 2 Dec 2015
|Conference||2nd IET International Conference on Intelligent Signal Processing|
|Period||1/12/15 → 2/12/15|
- polynomial eigenvalue decomposition
- broadband array processing
- space-time covariance matrix
- polynomial matrix
- matrix factorisation
- eigenvalues and eigenfunctions
- PEVD algorithms
FingerprintDive into the research topics of 'Impact of source model matrix conditioning on iterative PEVD algorithms'. Together they form a unique fingerprint.
- 1 Finished