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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/3ULAJ25
Repositorysid.inpe.br/mtc-m21c/2019/12.27.15.59   (restricted access)
Last Update2019:12.27.15.59.38 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2019/12.27.15.59.38
Metadata Last Update2019:12.28.22.12.55 (UTC) administrator
DOI10.1142/S0218127419501888
ISSN0218-1274
1793-6551
Citation KeyFreitasLaceMaca:2019:CoNeAp
TitleComplex networks approach for dynamical characterization of nonlinear systems
Year2019
MonthDec.
Access Date2024, May 28
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size552 KiB
2. Context
Author1 Freitas, Vander Luís de Souza
2 Lacerda, Juliana Cestari
3 Macau, Elbert Einstein Nehrer
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JGUT
Group1 CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
2 CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
3 LABAC-COCTE-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 vander.freitas@inpe.br
2
3 elbert.macau@inpe.br
JournalInternational Journal of Bifurcation and Chaos
Volume29
Number13
Pagese1950188
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)2019-12-27 15:59:38 :: simone -> administrator ::
2019-12-27 15:59:40 :: administrator -> simone :: 2019
2019-12-27 16:00:07 :: simone -> administrator :: 2019
2019-12-28 22:12:55 :: administrator -> simone :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsNonlinear dynamics
complex networks
time series analysis
AbstractBifurcation diagrams and Lyapunov exponents are the main tools for dynamical systems characterization. However, they are often computationally expensive and complex to calculate. We present two approaches for dynamical characterization of nonlinear systems via the generation of an undirected complex network that is built from their time series. Periodic windows and chaos can be detected by analyzing network statistics like average degree, density and betweenness centrality. Results are assessed in two discrete time nonlinear maps.
AreaCOMP
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Complex networks approach...
Arrangement 2urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CAP > Complex networks approach...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 27/12/2019 12:59 1.0 KiB 
4. Conditions of access and use
Languageen
Target Filefreitas_complex.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
Mirror Repositoryurlib.net/www/2017/11.22.19.04.03
Next Higher Units8JMKD3MGPCW/3ESGTTP
8JMKD3MGPCW/3F2PHGS
Citing Item Listsid.inpe.br/bibdigital/2013/10.12.22.16 5
sid.inpe.br/bibdigital/2013/09.22.23.14 4
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
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url
7. Description control
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