Comparative Speed Analysis of FastICA

FastICA is arguably one of the most widespread methods for independent component analysis. We focus on its deflation-based implementation, where the independent components are extracted one after another. The present contribution evaluates the method's speed in terms of the overall computational complexity required to reach a given source extraction performance. FastICA is compared with a simple modification referred to as RobustICA, which merely consists of performing exact line search optimization of the kurtosis-based contrast function. Numerical results illustrate the speed limitations of FastICA.

[1]  Ehud Weinstein,et al.  New criteria for blind deconvolution of nonminimum phase systems (channels) , 1990, IEEE Trans. Inf. Theory.

[2]  D. Donoho.  ON MINIMUM ENTROPY DECONVOLUTION , 1981 .

[3]  D. Godard,et al.  Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communication Systems , 1980, IEEE Trans. Commun..

[4]  Aapo Hyvärinen,et al.  A Fast Fixed-Point Algorithm for Independent Component Analysis of Complex Valued Signals , 2000, Int. J. Neural Syst..

[5]  Erkki Oja,et al.  Independent Component Analysis , 2001 .

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

[7]  P. Comon,et al.  Blind and semi-blind equalization based on the constant power criterion , 2005, IEEE Transactions on Signal Processing.

[8]  Pierre Comon.  Independent component analysis - a new concept? signal processing , 1994 .

[9]  Pierre Comon,et al.  Improved contrast dedicated to blind separation in communications , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[10]  William H. Press,et al.  Numerical recipes in C , 2002 .

[11]  A. Ferreol,et al.  Comparative performance analysis of eight blind source separation methods on radiocommunications signals , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[12]  P. Comon,et al.  Blind separation of discrete sources , 1998, IEEE Signal Processing Letters.

[13]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[14]  Jitendra K. Tugnait,et al.  Identification and deconvolution of multichannel linear non-Gaussian processes using higher order statistics and inverse filter criteria , 1997, IEEE Trans. Signal Process..

[15]  Pierre Comon,et al.  How fast is FastICA? , 2006, 2006 14th European Signal Processing Conference.

[16]  Tapani Ristaniemi,et al.  Advanced ICA-based receivers for block fading DS-CDMA channels , 2002, Signal Process..

[17]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[18]  Pierre Comon,et al.  Optimal Step-Size Constant Modulus Algorithm , 2008, IEEE Transactions on Communications.

[19]  Erkki Oja,et al.  Performance analysis of the FastICA algorithm and Crame/spl acute/r-rao bounds for linear independent component analysis , 2006, IEEE Transactions on Signal Processing.

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

[21]  D. Chakrabarti,et al.  A fast fixed - point algorithm for independent component analysis , 1997 .

[22]  Nathalie Delfosse,et al.  Adaptive blind separation of independent sources: A deflation approach , 1995, Signal Process..