@conference{10902/15871,
year = {2018},
url = {http://hdl.handle.net/10902/15871},
abstract = {An alternating optimization algorithm is presented and analyzed for identifying low-rank signal components, known in factor analysis terminology as common factors, that are correlated across two multiple-input multiple-output (MIMO) channels. The additive noise model at each of the MIMO channels consists of white uncorrelated noises of unequal variances plus a low-rank structured interference that is not correlated across the two channels. The low-rank components at each channel represent uncommon or channel-specific factors.},
organization = {The work of D. Ram´ırez was supported by the Ministerio de Economía, Industria y Competitividad (MINECO) and AEI/FEDER funds of the E.U., under grants TEC2013- 41718-R (OTOSIS), TEC2015-69648-REDC (COMONSENS Network), TEC2015-69868-C2-1-R (ADVENTURE), and CAIMAN (TEC2017-86921-C2-2-R) and The Comunidad de Madrid under grant S2013/ICE-2845 (CASI-CAM-CM). The work of I. Santamaria and S. Van Vaerenbergh was supported by MINECO and AEI/FEDER funds of the E.U., under grant TEC2016-75067-C4-4-R (CARMEN). The work of L. Scharf was supported in part by the National Science Foundation under grant CCF-1712788.},
publisher = {IEEE},
publisher = {52nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 2018, 1743-1747},
title = {An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors},
author = {Ramírez García, David and Santamaría Caballero, Luis Ignacio and Vaerenbergh, Steven van and Scharf, Louis L.},
}