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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/3QR7R95
Repositorysid.inpe.br/mtc-m21c/2018/04.02.11.56   (restricted access)
Last Update2018:04.02.11.56.27 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2018/04.02.11.56.27
Metadata Last Update2020:12.07.21.11.19 (UTC) administrator
DOI10.1142/S0218127418500086
ISSN0218-1274
1793-6551
Citation KeyCostaReiZouQuiMac:2018:ReDeEn
TitleRecurrence density enhanced complex networks for nonlinear time series analysis
Year2018
Monthjan.
Access Date2024, June 15
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size1635 KiB
2. Context
Author1 Costa, Diego G. de B.
2 Reis, Barbara Maximino da Fonseca
3 Zou, Yong
4 Quiles, Marcos G.
5 Macau, Elbert Einstein Nehrer
Resume Identifier1
2
3
4
5 8JMKD3MGP5W/3C9JGUT
Group1 CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
2 CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 East China Normal University
4 Universidade Federal de São Paulo (UNIFESP)
5 Universidade Federal de São Paulo (UNIFESP)
Author e-Mail Address1
2 barbara.reis@inpe.br
3 yzou@phy.ecnu.edu.cn
JournalInternational Journal of Bifurcation and Chaos
Volume28
Number1
Pagese1850008
Secondary MarkA1_ENGENHARIAS_IV A2_INTERDISCIPLINAR A2_ENGENHARIAS_III A2_ENGENHARIAS_I A2_BIODIVERSIDADE B1_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA B1_GEOCIÊNCIAS B1_ECONOMIA B1_CIÊNCIAS_AGRÁRIAS_I B2_CIÊNCIA_DA_COMPUTAÇÃO B4_ENSINO B4_CIÊNCIAS_BIOLÓGICAS_I B5_ASTRONOMIA_/_FÍSICA
History (UTC)2018-04-02 11:56:27 :: simone -> administrator ::
2018-04-02 11:56:27 :: administrator -> simone :: 2018
2018-04-02 11:57:14 :: simone -> administrator :: 2018
2018-07-04 17:51:11 :: administrator -> simone :: 2018
2018-08-07 13:13:10 :: simone -> administrator :: 2018
2020-12-07 21:11:19 :: administrator -> simone :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsRecurrence plot
recurrence networks
nonlinear time series
AbstractWe introduce a new method, which is entitled Recurrence Density Enhanced Complex Network (RDE-CN), to properly analyze nonlinear time series. Our method first transforms a recurrence plot into a figure of a reduced number of points yet preserving the main and fundamental recurrence properties of the original plot. This resulting figure is then reinterpreted as a complex network, which is further characterized by network statistical measures. We illustrate the computational power of RDE-CN approach by time series by both the logistic map and experimental fluid flows, which show that our method distinguishes different dynamics sufficiently well as the traditional recurrence analysis. Therefore, the proposed methodology characterizes the recurrence matrix adequately, while using a reduced set of points from the original recurrence plots.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CAP > Recurrence density enhanced...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 02/04/2018 08:56 1.0 KiB 
4. Conditions of access and use
Languageen
Target Filecosta_recurrence.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policydenypublisher allowfinaldraft
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Linking8JMKD3MGP3W34P/3L97U2B
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3F2PHGS
Citing Item Listsid.inpe.br/bibdigital/2013/10.12.22.16 7
sid.inpe.br/mtc-m21/2012/07.13.14.45.07 2
DisseminationWEBSCI; PORTALCAPES.
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
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