DIRECTLY ADJUSTING NODE'S IMPACTS TO REALIZE THE SYNCHRONIZATION OF COMPLEX NETWORKS

2010 ◽  
Vol 21 (06) ◽  
pp. 785-793 ◽  
Author(s):  
HAIFENG ZHANG ◽  
MING ZHAO ◽  
BINGHONG WANG
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Coupling Strength ◽  
Total Output ◽  
Output Coupling ◽  
Total Input

Most previous studies on the synchronization of complex networks were based on that each node managed to adjust its neighbors coupling strength to enhance synchronizability, i.e. each node tried to adjust its total input coupling strength in a proper way and the neighbor nodes were passively adjusted. From practical and engineering viewpoints, each node should manage to adjust its total output coupling strength to realize synchronization. Moreover, each node's total output coupling strength can be distributed to its neighbors with different proportions. In view of the above reasons, in this paper, we study the synchronization of complex networks under the assumptions that the total output coupling strength of each node is voluntarily/directly distributed to its neighbors with different proportions. What is more, we assume that the total output coupling strength of each node can be nonlinear to its degree. Our analysis and numerical simulations show that the synchronizability can be enhanced dramatically when the parameters are properly selected.

scholarly journals Adaptive Exponential Synchronization of Coupled Complex Networks on General Graphs

2013 ◽  
Vol 2013 ◽  
pp. 1-5
Author(s):  
Song Liu ◽  
Xianfeng Zhou ◽  
Wei Jiang ◽  
Yizheng Fan
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Coupling Strength ◽  
Weighted Graph ◽  
Complex Dynamical Networks ◽  
Adaptive Synchronization ◽  
Exponential Rate ◽  
General Graphs ◽  
Theoretical Results ◽  
Variable Coupling

We investigate the synchronization in complex dynamical networks, where the coupling configuration corresponds to a weighted graph. An adaptive synchronization method on general coupling configuration graphs is given. The networks may synchronize at an arbitrarily given exponential rate by enhancing the updated law of the variable coupling strength and achieve synchronization more quickly by adding edges to original graphs. Finally, numerical simulations are provided to illustrate the effectiveness of our theoretical results.

scholarly journals Cluster Synchronization of Nonlinearly Coupled Complex Networks via Pinning Control

2011 ◽  
Vol 2011 ◽  
pp. 1-23 ◽  
Author(s):  
Jianwen Feng ◽  
Jingyi Wang ◽  
Chen Xu ◽  
Francis Austin
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Coupling Strength ◽  
Topological Structure ◽  
Sufficient Conditions ◽  
Pinning Control ◽  
Cluster Synchronization ◽  
General Complex ◽  
Coupling Strengths ◽  
Theoretical Results

We consider a method for driving general complex networks into prescribed cluster synchronization patterns by using pinning control. The coupling between the vertices of the network is nonlinear, and sufficient conditions are derived analytically for the attainment of cluster synchronization. We also propose an effective way of adapting the coupling strengths of complex networks. In addition, the critical combination of the control strength, the number of pinned nodes and coupling strength in each cluster are given by detailed analysis cluster synchronization of a special topological structure complex network. Our theoretical results are illustrated by numerical simulations.

scholarly journals Topology Identification of Complex Network via Chaotic Ant Swarm Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Haipeng Peng ◽  
Lixiang Li ◽  
Jürgen Kurths ◽  
Shudong Li ◽  
Yixian Yang
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Complex Network ◽  
Parameter Optimization ◽  
Ant Algorithm ◽  
Structure Parameters ◽  
Topology Identification ◽  
Unknown Structure ◽  
Swarm Algorithm ◽  
Scientific Fields

Nowadays, the topology of complex networks is essential in various fields as engineering, biology, physics, and other scientific fields. We know in some general cases that there may be some unknown structure parameters in a complex network. In order to identify those unknown structure parameters, a topology identification method is proposed based on a chaotic ant swarm algorithm in this paper. The problem of topology identification is converted into that of parameter optimization which can be solved by a chaotic ant algorithm. The proposed method enables us to identify the topology of the synchronization network effectively. Numerical simulations are also provided to show the effectiveness and feasibility of the proposed method.

Coupling strength computation for chaotic synchronization of complex networks with multi-scroll attractors

2016 ◽  
Vol 275 ◽  
pp. 305-316 ◽  
Author(s):  
A.G. Soriano-Sánchez ◽  
C. Posadas-Castillo ◽  
M.A. Platas-Garza ◽  
C. Cruz-Hernández ◽  
R.M. López-Gutiérrez
Keyword(s):  
Complex Networks ◽  
Coupling Strength ◽  
Chaotic Synchronization

scholarly journals Energy use efficiency in soybean crops in different regions of Brazil

2020 ◽  
Vol 41 (6supl2) ◽  
pp. 2991-3010
Author(s):  
Roni Fernandes Guareschi ◽  
◽  
Marcio dos Reis Martins ◽  
Leonardo Fernandes Sarkis ◽  
Bruno José Rodrigues Alves ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Use ◽  
Calorific Value ◽  
Weather Conditions ◽  
Production Costs ◽  
Total Output ◽  
Soybean Crop ◽  
South Central ◽  
Total Input ◽  
Adverse Weather

The soybean crop in Brazil has been growing in area and productivity in recent years and the analysis of its energy efficiency is very important to guarantee the sustainability of the production system. Assessment of energy efficiency (EE) enables the evaluation of the sustainability of agrosystems, as well as decision-making regarding the reduction in production costs and negative environmental impacts. In this context, the objective of this study was to assess energy efficiency of soybean in different regions of Brazil. For this purpose, 29 areas of soybean across the major producing states were assessed. Energy inputs and outputs of agricultural operations and/or agricultural inputs were calculated by multiplying the amount used by their calorific value or energy coefficient at each stage of production. Energy efficiency was calculated as the ratio between the total output energy and the total input energy during the production process. For every MJ of energy consumed in the production of soybean crop, 6.1; 6.7; 7.1 and 7.2 MJ of energy were produced in the form of grain, respectively in the areas assessed in the Midwest, northeast, southeast and south regions of Brazil. Generally, the main energy expenditure on soybean cultivation in different regions of Brazil was with fertilizers, seeds and herbicides. The adverse weather conditions of the year / harvest evaluated in the south-central region of Brazil resulted in low soybean yields and consequently resulted in lower energy efficiency in these regions. The evaluation of energy efficiency in soybean crops to be representative must be carried out in different regions and edaphoclimatic conditions.

Control of amplitude death by coupling range in a network of fractional-order oscillators

2020 ◽  
Vol 34 (31) ◽  
pp. 2050303
Author(s):  
Rui Xiao ◽  
Zhongkui Sun
Keyword(s):  
Theoretical Analysis ◽  
Numerical Simulations ◽  
Fractional Order ◽  
Coupling Strength ◽  
Low Frequency ◽  
System Size ◽  
Coupled Systems ◽  
Amplitude Death ◽  
Function Relationship ◽  
The Relationship

We investigate the oscillating dynamics in a ring of network of nonlocally delay-coupled fractional-order Stuart-Landau oscillators. It is concluded that with the increasing of coupling range, the structures of death islands go from richness to simplistic, nevertheless, the area of amplitude death (AD) state is expanded along coupling delay and coupling strength directions. The increased coupling range can prompt the coupled systems with low frequency to occur AD. When system size varies, the area of death islands changes periodically, and the linear function relationship between periodic length and coupling range can be deduced. Thus, one can modulate the oscillating dynamics by adjusting the relationship between coupling range and system size. Furthermore, the results of numerical simulations are consistent with theoretical analysis.

ESTIMATION OF CONTROL ENERGY AND CONTROL STRATEGIES FOR COMPLEX NETWORKS

2015 ◽  
Vol 18 (07n08) ◽  
pp. 1550018 ◽  
Author(s):  
DINGJIE WANG ◽  
SUOQIN JIN ◽  
FANG-XIANG WU ◽  
XIUFEN ZOU
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Energy Cost ◽  
Control Strategies ◽  
Energy Costs ◽  
Theoretical Derivation ◽  
Complete Control ◽  
Undirected Network ◽  
Normal Networks ◽  
And Control

The controlling of complex networks is one of the most challenging problems in modern network science. Accordingly, the required energy cost of control is a fundamental and significant problem. In this paper, we present the theoretical analysis and numerical simulations to study the controllability of complex networks from the energy perspective. First, by combining theoretical derivation and numerical simulations, we obtain lower bounds of the maximal and minimal energy costs for an arbitrary normal network, which are related to the eigenvalues of the state transition matrix. Second, we deduce that controlling unstable normal networks is easier than controlling stable normal networks with the same size. Third, we demonstrate a tradeoff between the control energy and the average degree (or the maximum degree) of an arbitrary undirected network. Fourth, numerical simulations show that the energy cost is negatively correlated with the degree of nodes. Moreover, the combinations of control nodes with the greater sum of degree need less energy to implement complete control. Finally, we propose a multi-objective optimization model to obtain the control strategy, which not only ensures the fewer control nodes but also guarantees the less energy cost of control.

Resource network theory

2016 ◽  
Author(s):  
Жилякова ◽  
Liudmila Zhilyakova ◽  
Кузнецов ◽  
Oleg Kuznetsov
Keyword(s):  
Initial Conditions ◽  
Limit State ◽  
Operation Time ◽  
Total Output ◽  
Time Step ◽  
Resource Network ◽  
Output Capacity ◽  
High Resource ◽  
Total Input ◽  
Total Resource

We represent a resource network as a new model of spreading of uniform resources. A resource network is a directed graph, where edges have capacities. Any vertex can store an unlimited amount of resource. The network operates in discrete time. The total amount of resource throughout network operation time does not change. At time step t each vertex sends resource along the outgoing edges to adjacent vertices following one of the two rules. If its resource amount is not less than the sum of capacities of all its outgoing edges, the vertex gives away its total output capacity. Otherwise, the vertex gives away all its resource, distributing it proportionally to the capacities of outgoing edges. For every network, there exists a threshold value T of total resource. Network behavior is significantly different depending on its low or high resource. If a network has sources (vertices whose total input capacity is less than total output capacity) and receivers (whose total input exceeds total output), then with high total resource its surplus (over T) finally is redistributed among special receivers (attractors). We propose the matrix classification of networks based on graph structure and on capacities. Overall study scheme for all classes is the same. We find the limit state and flow vectors (or prove their absence) for different initial conditions and values of the total resource amount, wherein the difference in behavior with low and high resource is demonstrated. However, the methods and results for different classes of networks are significantly different.

scholarly journals Mean Square Synchronization of Stochastic Nonlinear Delayed Coupled Complex Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Chengrong Xie ◽  
Yuhua Xu ◽  
Dongbing Tong
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Invariance Principle ◽  
Sufficient Conditions ◽  
Stochastic Perturbation ◽  
Mean Square ◽  
Topology Identification ◽  
And Topology ◽  
Adaptive Laws ◽  
Weiner Process

We investigate the problem of adaptive mean square synchronization for nonlinear delayed coupled complex networks with stochastic perturbation. Based on the LaSalle invariance principle and the properties of the Weiner process, the controller and adaptive laws are designed to ensure achieving stochastic synchronization and topology identification of complex networks. Sufficient conditions are given to ensure the complex networks to be mean square synchronization. Furthermore, numerical simulations are also given to demonstrate the effectiveness of the proposed scheme.

scholarly journals Non-Markovianity over Ensemble Averages in Quantum Complex Networks

2017 ◽  
Vol 24 (04) ◽  
pp. 1740018 ◽  
Author(s):  
Johannes Nokkala ◽  
Sabrina Maniscalco ◽  
Jyrki Piilo
Keyword(s):  
Spectral Density ◽  
Harmonic Oscillator ◽  
Complex Networks ◽  
Transport Properties ◽  
Network Structure ◽  
Coupling Strength ◽  
Large Impact ◽  
Random Networks ◽  
Quantum Harmonic Oscillator ◽  
Different Types

We consider bosonic quantum complex networks as structured finite environments for a quantum harmonic oscillator and investigate the interplay between the network structure and its spectral density, excitation transport properties and non-Markovianity. After a review of the formalism used, we demonstrate how even small changes to the network structure can have a large impact on the transport of excitations. We then consider the non-Markovianity over ensemble averages of several different types of random networks of identical oscillators and uniform coupling strength. Our results show that increasing the number of interactions in the network tends to suppress the average non-Markovianity. This suggests that tree networks are the random networks optimizing this quantity.

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