Literature DB >> 17155589

Estimating topology of networks.

Dongchuan Yu1, Marco Righero, Ljupco Kocarev.   

Abstract

We suggest a method for estimating the topology of a network based on the dynamical evolution supported on the network. Our method is robust and can be also applied when disturbances and/or modeling errors are presented. Several examples with networks of phase oscillators, pulse-coupled Hindmarch-Rose neurons, and Lorenz oscillators are provided to illustrate our approach.

Year:  2006        PMID： 17155589     DOI： 10.1103/PhysRevLett.97.188701

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN： 0031-9007            Impact factor:   9.161


  17 in total

1.  Fundamental limitations of network reconstruction from temporal data.

Authors:  Marco Tulio Angulo; Jaime A Moreno; Gabor Lippner; Albert-László Barabási; Yang-Yu Liu
Journal:  J R Soc Interface       Date:  2017-02       Impact factor: 4.118

2.  Detecting synaptic connections in neural systems using compressive sensing.

Authors:  Yu Yang; Chuankui Yan
Journal:  Cogn Neurodyn       Date:  2021-11-20       Impact factor: 3.473

3.  Full reconstruction of simplicial complexes from binary contagion and Ising data.

Authors:  Huan Wang; Chuang Ma; Han-Shuang Chen; Ying-Cheng Lai; Hai-Feng Zhang
Journal:  Nat Commun       Date:  2022-06-01       Impact factor: 17.694

4.  Information flow in networks and the law of diminishing marginal returns: evidence from modeling and human electroencephalographic recordings.

Authors:  Daniele Marinazzo; Guorong Wu; Mario Pellicoro; Leonardo Angelini; Sebastiano Stramaglia
Journal:  PLoS One       Date:  2012-09-18       Impact factor: 3.240

5.  Inferring synaptic connectivity from spatio-temporal spike patterns.

Authors:  Frank Van Bussel; Birgit Kriener; Marc Timme
Journal:  Front Comput Neurosci       Date:  2011-02-01       Impact factor: 2.380

6.  Inferring network connectivity by delayed feedback control.

Authors:  Dongchuan Yu; Ulrich Parlitz
Journal:  PLoS One       Date:  2011-09-28       Impact factor: 3.240

7.  Causal information approach to partial conditioning in multivariate data sets.

Authors:  D Marinazzo; M Pellicoro; S Stramaglia
Journal:  Comput Math Methods Med       Date:  2012-05-21       Impact factor: 2.238

8.  Functional connectivity in a rhythmic inhibitory circuit using Granger causality.

Authors:  Tilman Kispersky; Gabrielle J Gutierrez; Eve Marder
Journal:  Neural Syst Circuits       Date:  2011-05-25

9.  Characterizing global evolutions of complex systems via intermediate network representations.

Authors:  Koji Iwayama; Yoshito Hirata; Kohske Takahashi; Katsumi Watanabe; Kazuyuki Aihara; Hideyuki Suzuki
Journal:  Sci Rep       Date:  2012-05-25       Impact factor: 4.379

10.  On the Inference of Functional Circadian Networks Using Granger Causality.

Authors:  Arya Pourzanjani; Erik D Herzog; Linda R Petzold
Journal:  PLoS One       Date:  2015-09-28       Impact factor: 3.240
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