A New Quadratic Matrix Inequality Approach to Robust Adaptive Beamforming for General-rank Signal Model

The worst-case robust adaptive beamforming problem for generalrank signal model is considered. This is a nonconvex problem, and an approximate version of it (by introducing a matrix decomposition on the presumed covariance matrix of the desired signal) has been studied in the literature. Herein the...

Celý popis

Podrobná bibliografie

Vydáno v:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 4335 - 4339
Hlavní autoři:	Huang, Yongwei, Vorobyov, Sergiy A., Luo, Zhi-Quan
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.05.2019
Témata:	Adaptation models Approximation algorithms Array signal processing Covariance matrices deterministic approximate algorithm general-rank signal model Linear matrix inequalities linear matrix inequality relaxation Matrix decomposition quadratic matrix inequality problem Robust adaptive beamforming Semidefinite programming Signal processing algorithms Signal to noise ratio Speech processing
ISSN:	2379-190X
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!