An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors
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AuthorRamírez García, David; Santamaría Caballero, Luis Ignacio; Van Vaerenbergh, Steven; Scharf, Louis L.
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.