arXiv subjects

Hui-Jie Yang

Publications and source records attributed to Hui-Jie Yang.

8 recordsLinked to original sources

arXiv2017

Exponential distance distribution of connected neurons in simulations of two-dimensional in vitro neural network development

The distribution of the geometric distances of connected neurons is a practical factor underlying neural networks in the brain. It can affect the brainś dynamic properties at the ground level. Karbowski derived a power-law decay distribution that has not yet been verified by experiment. In this work, we check its validity using simulations with a phenomenological model. Based on the in vitro two-dimensional development of neural networks in culture vessels by Ito, we match the synapse number saturation time to obtain suitable parameters for the development process, then determine the distribution of distances between connected neurons under such conditions. Our simulations obtain a clear exponential distribution instead of a power-law one, which indicates that Karbowski's conclusion is invalid, at least for the case of in vitro neural network development in two-dimensional culture vessels.

q-bio.NC↗

arXiv2007

The process of coevolutionary competitive exclusion: speciation, multifractality and power-laws in correlation

Competitive exclusion, a key principle of ecology, can be generalized to understand many other complex systems. Individuals under surviving pressure tend to be different from others, and correlations among them change correspondingly to the updating of their states. We show with numerical simulation that these aptitudes can contribute to group formation or speciation in social fields. Moreover, they can lead to power-law topological correlations of complex networks. By coupling updating states of nodes with variation of connections in a network, structural properties with power-laws and functions like multifractality, spontaneous ranking and evolutionary branching of node states can emerge out simultaneously from the present self-organized model of coevolutionary process.

physics.data-an↗

arXiv2007

Scale-invariance of human EEG signals in sleep

We investigate the dynamical properties of electroencephalogram (EEG) signals of human in sleep. By using a modified random walk method, We demonstrate that the scale-invariance is embedded in EEG signals after a detrending procedure. Further more, we study the dynamical evolution of probability density function (PDF) of the detrended EEG signals by nonextensive statistical modeling. It displays scale-independent property, which is markedly different from the turbulent-like scale-dependent PDF evolution.

physics.bio-ph↗

arXiv2006

Naming Game on small-world networks: the role of clustering structure

Naming Game is a recently proposed model for describing how a multi-agent system can converge towards a consensus state in a self-organized way. In this paper, we investigate this model on the so-called homogeneous small-world networks and focus on the influence of the triangular topology on the dynamics. Of all the topological quantities, the clustering coefficient is found to play a significant role in the dynamics of the Naming Game. On the one hand, it affects the maximum memory of each agent; on the other hand, it inhibits the growing of clusters in which agents share a common word, i.e., a larger clustering coefficient will cause a slower convergence of the system. We also find a quantitative relationship between clustering coefficient and the maximum memory.

physics.data-an↗

arXiv2006

Diffusion entropy analysis on the stride interval fluctuation of human gait

In this paper, the diffusion entropy technique is applied to investigate the scaling behavior of stride interval fluctuations of human gait. The scaling behavior of the stride interval of human walking at normal, slow and fast rate are similar; with the scale-invariance exponents in the interval $[0.663,0.955]$, of which the mean value is $0.821\pm0.011$. Dynamical analysis of these stride interval fluctuations reveals a self-similar pattern: Fluctuation at one time scale are statistically similar to those at multiple other time scales, at least over hundreds of steps, while the healthy subjects walk at their normal rate. The long-range correlations are observed during the spontaneous walking after the removal of the trend in the time series with Fourier filter. These findings uncover that the fractal dynamics of stride interval of human gait are normally intrinsic to the locomotor systems.

physics.bio-ph↗

arXiv2006

Relations between Average Distance, Heterogeneity and Network Synchronizability

By using the random interchanging algorithm, we investigate the relations between average distance, standard deviation of degree distribution and synchronizability of complex networks. We find that both increasing the average distance and magnifying the degree deviation will make the network synchronize harder. Only the combination of short average distance and small standard deviation of degree distribution that ensures strong synchronizability. Some previous studies assert that the maximal betweenness is a right quantity to estimate network synchronizability: the larger the maximal betweenness, the poorer the network synchronizability. Here we address an interesting case, which strongly suggests that the single quantity, maximal betweenness, may not give a comprehensive description of network synchronizability.

cond-mat.stat-mech↗

arXiv2005

Diffusion entropy analysis on the scaling behavior of financial markets

In this paper the diffusion entropy technique is applied to investigate the scaling behavior of financial markets. The scaling behaviors of four representative stock markets, Dow Jones Industrial Average, Standard&Poor 500, Heng Seng Index, and Shang Hai Stock Synthetic Index, are almost the same; with the scale-invariance exponents all in the interval $[0.92, 0.95]$. These results provide a strong evidence of the existence of long-rang correlation in financial time series, thus several variance-based methods are restricted for detecting the scale-invariance properties of financial markets. In addition, a parsimonious percolation model for stock markets is proposed, of which the scaling behavior agrees with the real-life markets well.

physics.soc-ph↗

arXiv2005

Efficient routing on scale-free networks based on local information

In this letter, we propose a new routing strategy with a single free parameter $α$ only based on local information of network topology. In order to maximize the packets handling capacity of underlying structure that can be measured by the critical point of continuous phase transition from free flow to congestion, the optimal value of $α$ is sought out. By investigating the distributions of queue length on each node in free state, we give an explanation why the delivering capacity of the network can be enhanced by choosing the optimal $α$. Furthermore, dynamic properties right after the critical point are also studied. Interestingly, it is found that although the system enters the congestion state, it still possesses partial delivering capability which do not depend on $α$. This phenomenon suggests that the capacity of the network can be enhanced by increasing the forwarding ability of small important nodes which bear severe congestion.

physics.soc-ph↗