Correntropy as a novel measure for nonlinearity tests
Signal Processing
Information preserving empirical mode decomposition for filtering field potentials
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
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This paper presents several improvements to the framework of information-preserving empirical mode decomposition (EMD). The basic framework was presented in our previous work [1]. The method decomposes a non-stationary neural response into a number of oscillatory modes varying in information content. After the spectral information analysis only few modes, taking part in stimulus coding, are retrieved for further analysis. The improvements and enhancement have been proposed for the steps involved in information quantification and modes extraction. An investigation has also been carried out for compression of retrieved informative modes of the neural signal in order to achieve a lower bit rate using the proposed framework. Experimental results are presented.