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Conference papers
Reliable gradient search directions for kurtosis-based deflationary ICA: Application to physiological signal processing.
Abstract : Efficient gradient search directions for the optimisation of the kurtosis-based deflationary RobustICA algorithm in the case of real-valued data are proposed in this paper. The proposed scheme employs, in the gradient-like algorithm typically used to optimise the considered kurtosis-based objective function, search directions computed from a more reliable approximation of the negentropy than the kurtosis. The proposed scheme inherits the exact line search of the conventional RobustICA for which a good convergence property through a given direction is guaranteed. The efficiency of the proposed scheme is evaluated in terms of estimation quality, the execution time and the iterations count as a function of the number of used sensors and for different signal to noise ratios in the contexts of non-invasive epileptic ElectroEncephaloGraphic (EEG) and Magnetic Resonance Spectroscopic (MRS) analysis. The obtained results show that the proposed approach offer the best estimation performance/iterations count and execution time trade-off, especially in the case of high number of sensors.
Cited literature [9 references]
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01624648
Contributor : Lotfi Senhadji Connect in order to contact the contributor
Submitted on : Thursday, October 26, 2017 - 3:54:51 PM
Last modification on : Friday, January 15, 2021 - 3:33:44 AM
Long-term archiving on: : Saturday, January 27, 2018 - 3:51:44 PM
Contributor : Lotfi Senhadji Connect in order to contact the contributor
Submitted on : Thursday, October 26, 2017 - 3:54:51 PM
Last modification on : Friday, January 15, 2021 - 3:33:44 AM
Long-term archiving on: : Saturday, January 27, 2018 - 3:51:44 PM
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Relable GR Search ICA.pdf
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