CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Detecting low-dimensional chaos in time series of finite length generated from discrete parameter processes
Authors
G. Gonzato
W. Marzocchi
F. Mulargia
Publication date
1 January 1996
Publisher
'Elsevier BV'
Doi
Cite
Abstract
One of the truly novel issues in the physics of the last decade is that some time series considered of stochastic origin might in fact be of a particular deterministic type, named "chaotic". Chaotic processes are essentially characterized by a low, rather than very high (as in stochastic processes), number of degrees of freedom. There has been a proliferation of attempts to provide efficient analytical tools to discriminate between chaos and stochasticity, but in most cases their practical utility is limited by the lack of knowledge of their effectiveness in realistic time series, i.e. of finite length and contaminated by noise. The present paper attempts to estimate the practical efficiency of a slightly modified Sugihara and May procedure [G. Sugihara and R.M. May, Nature 344 (1990) 734]. This is applied to synthetic finite time series generated from discrete parameter processes, providing rates of misidentification (obtained through simulations) for the most common stochastic processes (Gaussian, exponential, autoregressive, and periodic) and chaotic maps (logistic, Hénon, biological, Tent, trigonometric, and Ikeda). The procedure consists of comparing with a selected threshold the correlation between actual and predicted values one time step into the future as a function of the embedding dimension E. This procedure allows to infer the presence of low-dimensional chaos even on series of ∼ 50 units, and in presence of a noise level equal to ∼ 10% of the signal amplitude. We apply this method to the sequence of volcanic eruptions of Piton de La Fournaise volcano finding no evidence of low-dimensional chaos. © 1996 Elsevier Science B.V. All rights reserved
Similar works
Full text
Available Versions
Archivio della ricerca - Università degli studi di Napoli Federico II
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:www.iris.unina.it:11588/74...
Last time updated on 19/04/2019