@inproceedings{4f0ffd31af744c54be5ec9ecd8d3b79e,
title = "Data dimension reduction using krylov subspaces: Making adaptive beamformers robust to model order-determination",
abstract = "In this work, we present a class of low-complexity reduced-dimension adaptive beamformers constructed from expanding Krylov subspaces. We demonstrate how the data dimensionality reduction obtained from Krylov pre-processing decreases the sensitivity of reduced-rank adaptive beamforming techniques to incorrect model-order selection and lessens the computational complexity of systems involving large arrays with many elements. An important advantage of the proposed dimensionality reduction scheme is that it relieves reduced-rank methods from the stringent requirement on the precise model order determination.",
author = "Hongya Ge and Kirsteins, {Ivars P.} and Scharf, {Louis L.}",
note = "Copyright: Copyright 2008 Elsevier B.V., All rights reserved.; 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 ; Conference date: 14-05-2006 Through 19-05-2006",
year = "2006",
language = "English (US)",
isbn = "142440469X",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "IV1001--IV1004",
booktitle = "2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings",
}