On the performance indices of ICA and blind source separation

For assessing the separation performance (quality and accuracy) of ICA estimators, several performance indices have been introduced in the literature. The purpose of this note is to outline, review and study the properties of performance indices as well as propose some new ones. Special emphasis is put on the properties that such performance indices ought to satisfy. We categorize the indices in two separate groups that differ in the approaches they deploy in measuring the closeness of the achieved source separation to the ideal case and point out some inherent relations between the indices in these categories.

[1]  Hannu Oja,et al.  Complex-valued ICA based on a pair of generalized covariance matrices , 2008, Comput. Stat. Data Anal..

[2]  Noboru Ohnishi,et al.  A survey of the performance indexes of ICA algorithms , 2002 .

[3]  J. Cardoso,et al.  Blind beamforming for non-gaussian signals , 1993 .

[4]  Visa Koivunen,et al.  Maximum likelihood estimation of ICA model for wide class of source distributions , 2000, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501).

[5]  Visa Koivunen,et al.  Identifiability, separability, and uniqueness of linear ICA models , 2004, IEEE Signal Processing Letters.

[6]  Seungjin Choi,et al.  Independent Component Analysis , 2009, Handbook of Natural Computing.

[7]  Pauliina Ilmonen,et al.  Characteristics of multivariate distributions and the invariant coordinate system , 2010 .

[8]  Esa Ollila.  On the robustness of the deflation-based FastICA estimator , 2009, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing.

[9]  Esa Ollila,et al.  The Deflation-Based FastICA Estimator: Statistical Analysis Revisited , 2010, IEEE Transactions on Signal Processing.

[10]  Andrzej Cichocki,et al.  A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.

[11]  J. Cardoso.  On the Performance of Orthogonal Source Separation Algorithms , 1994 .

[12]  Klaus Nordhausen,et al.  A New Performance Index for ICA: Properties, Computation and Asymptotic Analysis , 2010, LVA/ICA.

[13]  Moeness G. Amin,et al.  Jammer mitigation in spread spectrum communications using blind sources separation , 2000, Signal Process..

[14]  Aapo Hyvärinen,et al.  Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.

[15]  Scott C. Douglas,et al.  Fixed-Point Algorithms for the Blind Separation of Arbitrary Complex-Valued Non-Gaussian Signal Mixtures , 2007, EURASIP J. Adv. Signal Process..