Literature DB >> 16907306

Estimating the Shannon entropy: recurrence plots versus symbolic dynamics.

Christophe Letellier1.   

Abstract

Recurrence plots were first introduced to quantify the recurrence properties of chaotic dynamics. A few years later, the recurrence quantification analysis was introduced to transform graphical representations into statistical analysis. Among the different measures introduced, a Shannon entropy was found to be correlated with the inverse of the largest Lyapunov exponent. The discrepancy between this and the usual interpretation of a Shannon entropy is solved here by using a new definition--still based on the recurrence plots--and it is verified that this new definition is correlated with the largest Lyapunov exponent, as expected from the Pesin conjecture. A comparison with a Shannon entropy computed from symbolic dynamics is also provided.

Year:  2006        PMID: 16907306     DOI: 10.1103/PhysRevLett.96.254102

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  4 in total

1.  A symbolic network-based nonlinear theory for dynamical systems observability.

Authors:  Christophe Letellier; Irene Sendiña-Nadal; Ezequiel Bianco-Martinez; Murilo S Baptista
Journal:  Sci Rep       Date:  2018-02-28       Impact factor: 4.379

2.  Robust Detection of COVID-19 in Cough Sounds: Using Recurrence Dynamics and Variable Markov Model.

Authors:  Pauline Mouawad; Tammuz Dubnov; Shlomo Dubnov
Journal:  SN Comput Sci       Date:  2021-01-12

3.  Alternate Entropy Computations by Applying Recurrence Matrix Masking.

Authors:  Charles L Webber
Journal:  Entropy (Basel)       Date:  2021-12-23       Impact factor: 2.524

4.  Electrical coupling controls dimensionality and chaotic firing of inferior olive neurons.

Authors:  Huu Hoang; Eric J Lang; Yoshito Hirata; Isao T Tokuda; Kazuyuki Aihara; Keisuke Toyama; Mitsuo Kawato; Nicolas Schweighofer
Journal:  PLoS Comput Biol       Date:  2020-07-30       Impact factor: 4.475

  4 in total

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