The Tsallis entropy of natural information

Robert Sneddon

Physica A: Statistical Mechanics and its Applications, 2007, vol. 386, issue 1, 101-118

Abstract: Estimating the information contained in natural data, such as electroencephalography data, is unusually difficult because the relationship between the physical data and the information that it encodes is unknown. This unknown relationship is often called the encoding problem. The present work provides a solution to this problem by deriving a method to estimate the Tsallis entropy in natural data. The method is based on two findings. The first finding is that the physical instantiation of any information event, that is, the physical occurrence of a symbol of information, must begin and end at a discontinuity or critical point (maximum, minimum, or saddle point) in the data. The second finding is that, in certain data types such as the encephalogram (EEG), the variance within of an EEG waveform event is directly proportional to its probability of occurrence.

Keywords: Information; Tsallis; Entropy; EEG; Electroencephalography; Alzheimer's; ADRD; Encoding; Memory; Non extensive (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:386:y:2007:i:1:p:101-118

DOI: 10.1016/j.physa.2007.05.065

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