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.
The UNT College of Arts and Sciences educates students in traditional liberal arts, performing arts, sciences, professional, and technical academic programs. In addition to its departments, the college includes academic centers, institutes, programs, and offices providing diverse courses of study.
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.
Physical Description
28 p.
Notes
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
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.
This article is part of the following collection of related materials.
UNT Scholarly Works
Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.
Allegrini, Paolo; Benci, V. (Vieri); Grigolini, Paolo; Hamilton, P.; Ignaccolo, Massimiliano; Menconi, Giulia et al.Compression and Diffusion: A Joint Approach to Detect Complexity,
article,
February 1, 2003;
[New York, New York].
(https://digital.library.unt.edu/ark:/67531/metadc139462/:
accessed March 19, 2024),
University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu;
crediting UNT College of Arts and Sciences.