Abstract
This paper presents a concept of using the empirical mode decomposition (EMD) as a filtering tool to extract information-preserving intrinsic mode functions (IMFs) in an adaptive manner. The approach is tested on several local field potentials (LFPs) and information quantification is carried out in spectral domain using Shannon's Information. The study suggests that not all IMFs are information carriers. It is found that the 1st IMF carries 60-80% of the total information from original LFP and few informative IMFs are usually the main information carriers. Adding more IMFs does not increase the information level. For different datasets, the order of the informative IMFs varies and by using information preserving EMD, only few IMFs are retained to provide a simplified representation of underlying oscillations contained in LFPs. © 2009 Springer Berlin Heidelberg.
| Original language | English |
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| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci. |
| Pages | 226-233 |
| Number of pages | 7 |
| Volume | 5788 |
| DOIs | |
| Publication status | Published - 2009 |
| Event | 10th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2009 - Burgos Duration: 1 Jul 2009 → … |
Conference
| Conference | 10th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2009 |
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| City | Burgos |
| Period | 1/07/09 → … |