ordinal patterns, entropy, and eeg

Clicks: 313
ID: 163026
2014
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
In this paper we illustrate the potential of ordinal-patterns-based methods for analysis of real-world data and, especially, of electroencephalogram (EEG) data. We apply already known (empirical permutation entropy, ordinal pattern distributions) and new (empirical conditional entropy of ordinal patterns, robust to noise empirical permutation entropy) methods for measuring complexity, segmentation and classification of time series.
Reference Key
keller2014entropyordinal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Karsten Keller;Anton M. Unakafov;Valentina A. Unakafova
Journal European journal of medicinal chemistry
Year 2014
DOI
10.3390/e16126212
URL
http://www.mdpi.com/1099-4300/16/12/6212
Keywords
Segmentation clustering approximate entropy sample entropy permutation entropy

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.