Independent vector analysis for convolutive blind noncircular source separation

Independent vector analysis (IVA), an extension of independent component analysis (ICA) from univariate components to multivariate components, is a method to tackle blind source separation (BSS) in frequency domain. IVA utilizes both the statistical independence among multivariate signals and the statistical inner dependency of each multivariate signal. However, so far there is no research on IVA for convolutive mixtures of noncircular sources. In this study, we focus on this problem and propose noncircular independent vector analysis (nc-IVA) algorithm, by deriving a new fixed-point algorithm that uses the information of pseudo-covariance matrix in each frequency bin. This modification provides more widely application scenarios with noncircular sources. Simulations demonstrate the effectiveness of our proposed method. (C) 2012 Elsevier B.V. All rights reserved.