Probability and statistics
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
A fast fixed-point algorithm for independent component analysis
Neural Computation
Adaptive processing of blind source separation through 'ICA with OS'
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01
Blind spatial multiplexing using order statistics for time-varying channels
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
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In this paper we propose an alternative statistical Gaussianit y measure whose optimization provides the extraction of one non-gaussian independent component at each stage of an ICA procedure; this measure is based on the Cumulative Density Function (cdf) instead of traditional distribution distances over Probability Density Functions (pdf's). Additionally, a novel multistage-deflation algorithm is proposed in order to perform ICA in multidimensional scenarios very efficiently; although this approach can be applied to any multistage ICA method, we have developed it to speed up our ICA procedure based on Order Statistics (OS). The algorithm consists on a gradien tlearning rule plus an orthonormalization projection technique that decreases the vector space dimension progressively.