relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2484/
title: Generalized minimum noise subspace for array processing
creator: Nguyen, Viet Dung
creator: Abed-Meraim, Karim
creator: Nguyen, Linh Trung
creator: Weber, Rodolphe
subject: Electronics and Communications
subject: ISI-indexed journals
description: Based on the minimum noise subspace (MNS) method previously introduced in the context of blind channel identification, generalized minimum noise subspace (GMNS) is proposed in this paper for array processing that generalizes MNS with respect to the availability of only a fixed number of parallel computing units. Different batch and adaptive algorithms are then introduced for fast and parallel computation of signal (principal) and noise (minor) subspaces. The computational complexity of GMNS and its related estimation accuracy are investigated by simulated experiments and a real-life experiment in radio astronomy. It is shown that GMNS represents an excellent tradeoff between the computational gain and the subspace estimation accuracy, as compared to several standard subspace methods.
publisher: IEEE
date: 2017-07
type: Article
type: PeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2484/2/Generalized%20Minimum%20Noise%20Subspace%20For%20Array%20Processing_Dung2017.pdf
identifier:   Nguyen, Viet Dung and Abed-Meraim, Karim and Nguyen, Linh Trung and Weber, Rodolphe  (2017) Generalized minimum noise subspace for array processing.  IEEE Transactions on Signal Processing, 65  (14).   pp. 3789-3802.  ISSN 1053-587X     
relation: http://ieeexplore.ieee.org/document/7903711/