Results 141 to 150 of about 343,367 (193)

Regional and cannabis-related differences in prefrontal multiscale entropy of resting-state EEG. [PDF]

Clin Neurophysiol Pract
Creel WT, Brenner CA, Hartman RE.
europepmc   +1 more source

EEG-Pype: An accessible MNE-Python pipeline with graphical user interface for preprocessing and analysis of resting-state electroencephalography data. [PDF]

PLoS Comput Biol
Lodema DY, van Dellen HJ, de Haan W, van Hest M, Hillebrand A, van Dellen E.   +5 more
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Entropy measures based on Nirmala coindices for silicon carbide molecular graphs. [PDF]

Sci Rep
Numan M, Aabid S, Ahmad S, Zidan AM, Hamoud AA.   +4 more
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Quantifying coupling and causality in dynamic bivariate systems: a unified framework for time-domain, spectral, and information-theoretic analysis. [PDF]

Front Netw Physiol
Sparacino L, Pinto H, Barà C, Antonacci Y, Pernice R, Rocha AP, Faes L.   +6 more
europepmc   +1 more source

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Beyond randomness: Evaluating measures of information entropy in binary series

Physical Review E, 2022
The enormous amount of currently available data demands efforts to extract meaningful information. For this purpose, different measurements are applied, including Shannon's entropy, permutation entropy, and the Lempel-Ziv complexity. These methods have been used in many applications, such as pattern recognition, series classification, and several other
Mariana Sacrini Ayres Ferraz, Alexandre Hiroaki Kihara   +1 more
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Entropy as a measure of database information

[1990] Proceedings of the Sixth Annual Computer Security Applications Conference, 2002
An estimate of the information a database contains and the quantification of the vulnerability of that database to compromise by inferential methods is discussed. Such a measure could be used to evaluate the deterrent value of extant protection methods and provide a measure of the potential for inferential compromise through the use of one of the known
E.A. Unger, L. Harn, V. Kumar
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Information‐theoretical entropy as a measure of sequence variability

Proteins: Structure, Function, and Bioinformatics, 1991
AbstractWe propose the use of the information‐theoretical entropy, S = −Σpi log2 Pi, as a measure of variability at a given position in a set of aligned sequences. pi stands for the fraction of times the i‐th type appears at a position. For protein sequences, the sum has up to 20 terms, for nucleotide sequences, up to 4 terms, and for codon sequences ...
P S, Shenkin, B, Erman, L D, Mastrandrea
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