Compression and Diffusion: A Joint Approach to Detect Complexity

Description:

Article discussing a joint approach to detect complexity by combining the Compression Algorithm Sensitive To Regularity (CASToRe) and Complex Analysis of Sequences via Scaling AND Randomness Assessment (CASSANDRA) procedures.

Creator(s):
Creation Date: February 2003
Partner(s):
UNT College of Arts and Sciences
Collection(s):
UNT Scholarly Works
Usage:
Total Uses: 29
Past 30 days: 0
Yesterday: 0
Creator (Author):
Allegrini, Paolo

University of North Texas; Istituto di Linguistica Computazionale del CNR

Creator (Author):
Benci, V. (Vieri)

Università di Pisa

Creator (Author):
Grigolini, Paolo

University of North Texas; Università di Pisa; Istituto di Biofisica del CNR

Creator (Author):
Hamilton, P.

Texas Woman's University

Creator (Author):
Ignaccolo, Massimiliano

University of North Texas

Creator (Author):
Menconi, Giulia

Università di Pisa

Creator (Author):
Palatella, Luigi

Università di Pisa

Creator (Author):
Raffaelli, G.

International School for Advanced Studies

Creator (Author):
Scafetta, Nicola

University of North Texas

Creator (Author):
Virgilio, M.

Università di Pisa

Creator (Author):
Yang, J.

University of North Texas

Publisher Info:
Publisher Name: Elsevier Science Ltd.
Place of Publication: [Amsterdam, Netherlands]
Date(s):
  • Creation: February 2003
Description:

Article discussing a joint approach to detect complexity by combining the Compression Algorithm Sensitive To Regularity (CASToRe) and Complex Analysis of Sequences via Scaling AND Randomness Assessment (CASSANDRA) procedures.

Degree:
Department: Physics
Note:

This is the preprint version of the article. Reprinted with permission from Elsevier Science Ltd., all rights reserved. The final definitive version is available here: http://dx.doi.org/10.1016/S0960-0779(02)00136-4

Note:

Abstract: The adoption of the Kolmogorov-Sinai (KS) entropy is becoming a popular research tool among physicists, especially when applied to a dynamical system fitting the conditions of validity of the Pesin theorem. The study of time series that are a manifestation of system dynamics whose rules are either unknown or too complex for a mathematical treatment, is still a challenge since the KS entropy is not computable, in general, in that case. Here the authors present a plan of action based on the joint action of two procedures, both related to the KS entropy, but compatible with computer implementation through fast and efficient programs. The former procedure, called Compression Algorithm Sensitive To Regularity (CASToRe), establishes the amount of order by the numerical evaluation of algorithmic compressibility. The latter, called Complex Analysis of Sequences via Scaling AND Randomness Assessment (CASSANDRA), establishes the complexity degree through the numerical evaluation of the strength of an anomalous effect. This is the departure, of the diffusion process generated by the observed fluctuations, from ordinary Brownian motion. The CASSANDRA algorithm shares with CASToRe a connection with the Kolmogorov complexity. This makes both algorithms especially suitable to study the transition from dynamics to thermodynamics, and the case of non-stationary time series as well. The benefit of the joint action of these two methods is proven by the analysis of artificial sequences with the same main properties as the real time series to which the joint use of these two methods will be applied in future research work.

Physical Description:

28 p.

Language(s):
Subject(s):
Keyword(s): compression | diffusion | Kolmogorov-Sinai entropy
Source: Chaos, Solitons and Fractals, 2003, Amsterdam: Elsevier Science Ltd., pp. 517-535
Partner:
UNT College of Arts and Sciences
Collection:
UNT Scholarly Works
Identifier:
  • DOI: 10.1016/S0960-0779(02)00136-4 |
  • ARK: ark:/67531/metadc139462
Resource Type: Article
Format: Text
Rights:
Access: Public
Citation:
Publication Title: Chaos, Solitons and Fractals
Volume: 15
Issue: 3
Page Start: 517
Page End: 535
Peer Reviewed: Yes