@inproceedings{0ebe2b0a54384baea6cd6114ec2d8264,
title = "Signal detection in para complex normal noise",
abstract = "In this paper we address target detection in correlated non-Gaussian noise. We introduce a powerful class of multivariate complex valued distribution that allows us to specify flexible non-Gaussian marginals, as well as correlation between the variables, while preserving circular symmetry. For noise belonging to this class, we study the fundamental problem of signal detection under different settings, and develop the needed (generalized) likelihood ratio tests. We also consider the problem of estimation of the noise parameters, and derive the maximum likelihood formulations. We compare the performance of the proposed methods using numerical simulations on synthetic data, and demonstrate the importance of using both correlations and non-Gaussiantiy.",
keywords = "Circular symmetry, copula, detection, non-Gaussian",
author = "Yonatan Woodbridge and Gal Elidan and Ami Wiesel",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 ; Conference date: 20-03-2016 Through 25-03-2016",
year = "2016",
month = may,
day = "18",
doi = "10.1109/ICASSP.2016.7472483",
language = "الإنجليزيّة",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4274--4278",
booktitle = "2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings",
address = "الولايات المتّحدة",
}