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The second order sequential best rotation (SBR2) algorithm is a popular algorithm to decompose a parahermitian matrix into approximated polynomial eigenvalues and eigen-vectors. The work horse behind SBR2 is a Givens rotation interspersed by delay operations. In this paper, we investigate and analyse the application of a fast Givens rotation in order to reduce the computation complexity of SBR2. The proposed algorithm inherits the SBR2's proven convergence to a diagonalised and spectrally majorised solution for the polynomial eigenvalues. We provide some analysis and examples for the execution speed of this fast Givens-based SBR2 compared to a standard SBR2 implementation.
|Number of pages||5|
|Publication status||Published - 15 Sep 2021|
|Event||International Conference in Sensor Signal Processing for Defence: from Sensor to Decision - Edinburgh, United Kingdom|
Duration: 14 Sep 2021 → 15 Sep 2021
Conference number: 10
|Conference||International Conference in Sensor Signal Processing for Defence|
|Period||14/09/21 → 15/09/21|
- sequential best rotation (SBR2)
- Givens rotation
- polynomial eigenvalues
- broadband signals
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