scholarly journals Information theoretical methods for complex network structure reconstruction

2013 ◽  
Vol 1 (1) ◽  
Author(s):  
Enrique Hernández-Lemus ◽  
Jesús M Siqueiros-García
Keyword(s):  
Complex Network ◽  
Network Structure ◽  
Theoretical Methods ◽  
Structure Reconstruction

Complex network structure of flocks in the Vicsek Model with Vectorial Noise

2014 ◽  
Vol 25 (03) ◽  
pp. 1350095 ◽  
Author(s):  
Gabriel Baglietto ◽  
Ezequiel V. Albano ◽  
Julián Candia
Keyword(s):  
Phase Transition ◽  
Complex Network ◽  
Network Structure ◽  
Time Step ◽  
Vicsek Model ◽  
Disorder Phase Transition ◽  
First Order ◽  
Direction Of Movement ◽  
Long Range Ordering ◽  
Influence Of Noise

In the Vicsek Model (VM), self-driven individuals try to adopt the direction of movement of their neighbors under the influence of noise, thus leading to a noise-driven order–disorder phase transition. By implementing the so-called Vectorial Noise (VN) variant of the VM (i.e. the VM-VN model), this phase transition has been shown to be discontinuous (first-order). In this paper, we perform an extensive complex network study of VM-VN flocks and show that their topology can be described as highly clustered, assortative, and nonhierarchical. We also study the behavior of the VM-VN model in the case of "frozen flocks" in which, after the flocks are formed using the full dynamics, particle displacements are suppressed (i.e. only rotations are allowed). Under this kind of restricted dynamics, we show that VM-VN flocks are unable to support the ordered phase. Therefore, we conclude that the particle displacements at every time-step in the VM-VN dynamics are a key element needed to sustain long-range ordering throughout.

Robust network structure reconstruction based on Bayesian compressive sensing

2019 ◽  
Vol 29 (9) ◽  
pp. 093119
Author(s):  
Keke Huang ◽  
Yang Jiao ◽  
Chen Liu ◽  
Wenfeng Deng ◽  
Zhen Wang
Keyword(s):  
Compressive Sensing ◽  
Network Structure ◽  
Structure Reconstruction ◽  
Robust Network

SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction

2020 ◽  
Vol 126 ◽  
pp. 143-152
Author(s):  
Keke Huang ◽  
Shuo Li ◽  
Penglin Dai ◽  
Zhen Wang ◽  
Zhaofei Yu
Keyword(s):  
Network Structure ◽  
Denoising Autoencoder ◽  
Game Dynamics ◽  
Structure Reconstruction

scholarly journals Complex Network Structure of Flocks in the Standard Vicsek Model

2013 ◽  
Vol 153 (2) ◽  
pp. 270-288 ◽  
Author(s):  
Gabriel Baglietto ◽  
Ezequiel V. Albano ◽  
Julián Candia
Keyword(s):  
Complex Network ◽  
Network Structure ◽  
Vicsek Model

Quantitative Anatomical Evidence for a Dorsoventral and Rostrocaudal Segregation within the Nonhuman Primate Frontal Cortex

2018 ◽  
Vol 30 (3) ◽  
pp. 353-364 ◽  
Author(s):  
Robert S. Blumenfeld ◽  
Daniel P. Bliss ◽  
Mark D'Esposito
Keyword(s):  
White Matter ◽  
Frontal Cortex ◽  
Community Detection ◽  
Network Structure ◽  
Nonhuman Primate ◽  
Theoretical Methods ◽  
Rostrocaudal Axis ◽  
Anatomical Evidence

The intrinsic white matter connections of the frontal cortex are highly complex, and the organization of these connections is not fully understood. Quantitative graph-theoretical methods, which are not solely reliant on human observation and interpretation, can be powerful tools for describing the organizing network principles of frontal cortex. Here, we examined the network structure of frontal cortical subregions by applying graph-theoretical community detection analyses to a graph of frontal cortex compiled from over 400+ macaque white-matter tracing studies. We find evidence that the lateral frontal cortex can be partitioned into distinct modules roughly organized along the dorsoventral and rostrocaudal axis.

Study on the Formation and Repeated Opening Mechanism of Ground Fissures under the Role of Surface Water

2011 ◽  
Vol 243-249 ◽  
pp. 3238-3243
Author(s):  
Zhen Wei Jiang ◽  
Qi Yao Wang
Keyword(s):  
Surface Water ◽  
Theoretical Analysis ◽  
Complex Network ◽  
Network Structure ◽  
Water Loss ◽  
Vertical Displacement ◽  
Hydraulic Pressure ◽  
Ground Fissures ◽  
Loess Region

The role of surface water is also the main reason for the formation and development of ground fissures. Five mechanisms were obtained on the formation of ground fissures under the role of surface water in the loess region through theoretical analysis, i.e., fissuring mechanism induced by loess collapsible deformation; that induced by dissolution and suffosion; that induced by water-loss shrinkage; that induced by hydraulic pressure; that induced by humidification and softening. As the role of surface water had certain phased and periodic characteristics, repeated fissuring mechanism of ground fissures was analyzed. Consequently, it could be known that the repeated fissuring of ground fissures under the role of surface water was mainly shown as horizontal openness and closure with little vertical displacement, and fissures were intersected and cross-cut with each other to form a complex network structure.

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