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Sample records for robust network synchronization

  1. Robust adaptive synchronization of general dynamical networks ...

    Indian Academy of Sciences (India)

    Robust adaptive synchronization; dynamical network; multiple delays; multiple uncertainties. ... Networks such as neural networks, communication transmission networks, social rela- tionship networks etc. ..... a very good effect. Pramana – J.

  2. Robust adaptive synchronization of general dynamical networks ...

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose ...

  3. Robust Synchronization in an E/I Network with Medium Synaptic Delay and High Level of Heterogeneity

    International Nuclear Information System (INIS)

    Han Fang; Wang Zhi-Jie; Gong Tao; Fan Hong

    2015-01-01

    It is known that both excitatory and inhibitory neuronal networks can achieve robust synchronization only under certain conditions, such as long synaptic delay or low level of heterogeneity. In this work, robust synchronization can be found in an excitatory/inhibitory (E/I) neuronal network with medium synaptic delay and high level of heterogeneity, which often occurs in real neuronal networks. Two effects of post-synaptic potentials (PSP) to network synchronization are presented, and the synaptic contribution of excitatory and inhibitory neurons to robust synchronization in this E/I network is investigated. It is found that both excitatory and inhibitory neurons may contribute to robust synchronization in E/I networks, especially the excitatory PSP has a more positive effect on synchronization in E/I networks than that in excitatory networks. This may explain the strong robustness of synchronization in E/I neuronal networks. (paper)

  4. Robust networked H∞ synchronization of nonidentical chaotic Lur'e systems

    International Nuclear Information System (INIS)

    Yang De-Dong

    2014-01-01

    We mainly investigate the robust networked H ∞ synchronization problem of nonidentical chaotic Lur'e systems. In the design of the synchronization scheme, some network characteristics, such as nonuniform sampling, transmission-induced delays, and data packet dropouts, are considered. The parameters of master—slave chaotic Lur'e systems often allow differences. The sufficient condition in terms of linear matrix inequality (LMI) is obtained to guarantee the dissipative synchronization of nonidentical chaotic Lur'e systems in network environments. A numerical example is given to illustrate the validity of the proposed method. (general)

  5. Robust synchronization of a class of chaotic networks

    Czech Academy of Sciences Publication Activity Database

    Čelikovský, Sergej; Lynnyk, Volodymyr; Chen, G.

    2013-01-01

    Roč. 350, č. 10 (2013), s. 2936-2948 ISSN 0016-0032 R&D Projects: GA ČR(CZ) GAP103/12/1794 Institutional support: RVO:67985556 Keywords : generalized Lorenz system * robust synchronization * dynamical complex network Subject RIV: BC - Control Systems Theory Impact factor: 2.260, year: 2013 http://library.utia.cas.cz/separaty/2013/TR/celikovsky-0398127.pdf

  6. Robust transient stabilisation problem for a synchronous generator in a power network

    Science.gov (United States)

    Verrelli, C. M.; Damm, G.

    2010-04-01

    The robust transient stabilisation problem (with stability proof€) of a synchronous generator in an uncertain power network with transfer conductances is rigorously formulated and solved. The generator angular speed and electrical power are required to be kept close, when mechanical and electrical perturbations occur, to the synchronous speed and mechanical input power, respectively, while the generator terminal voltage is to be regulated, when perturbations are removed, to its pre-fault reference constant value. A robust adaptive nonlinear feedback control algorithm is designed on the basis of a third-order model of the synchronous machine: only two system parameters (synchronous machine damping and inertia constants) along with upper and lower bounds on the remaining uncertain ones are supposed to be known. The conditions to be satisfied by the remote network dynamics for guaranteeing ℒ2 and ℒ∞ robustness and asymptotic relative speed and voltage regulation to zero are weaker than those required by the single machine-infinite bus approximation: dynamic interactions between the local deviations of the generator states from the corresponding equilibrium values and the remote generators states are allowed.

  7. Robust Adaptive Exponential Synchronization of Stochastic Perturbed Chaotic Delayed Neural Networks with Parametric Uncertainties

    Directory of Open Access Journals (Sweden)

    Yang Fang

    2014-01-01

    Full Text Available This paper investigates the robust adaptive exponential synchronization in mean square of stochastic perturbed chaotic delayed neural networks with nonidentical parametric uncertainties. A robust adaptive feedback controller is proposed based on Gronwally’s inequality, drive-response concept, and adaptive feedback control technique with the update laws of nonidentical parametric uncertainties as well as linear matrix inequality (LMI approach. The sufficient conditions for robust adaptive exponential synchronization in mean square of uncoupled uncertain stochastic chaotic delayed neural networks are derived in terms of linear matrix inequalities (LMIs. The effect of nonidentical uncertain parameter uncertainties is suppressed by the designed robust adaptive feedback controller rapidly. A numerical example is provided to validate the effectiveness of the proposed method.

  8. Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

    Science.gov (United States)

    Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

    2018-03-01

    In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

  9. Robust output synchronization of heterogeneous nonlinear agents in uncertain networks.

    Science.gov (United States)

    Yang, Xi; Wan, Fuhua; Tu, Mengchuan; Shen, Guojiang

    2017-11-01

    This paper investigates the global robust output synchronization problem for a class of nonlinear multi-agent systems. In the considered setup, the controlled agents are heterogeneous and with both dynamic and parametric uncertainties, the controllers are incapable of exchanging their internal states with the neighbors, and the communication network among agents is defined by an uncertain simple digraph. The problem is pursued via nonlinear output regulation theory and internal model based design. For each agent, the input-driven filter and the internal model compose the controller, and the decentralized dynamic output feedback control law is derived by using backstepping method and the modified dynamic high-gain technique. The theoretical result is applied to output synchronization problem for uncertain network of Lorenz-type agents. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Robust synchronization analysis in nonlinear stochastic cellular networks with time-varying delays, intracellular perturbations and intercellular noise.

    Science.gov (United States)

    Chen, Po-Wei; Chen, Bor-Sen

    2011-08-01

    Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. Robust synchronization of delayed neural networks based on adaptive control and parameters identification

    International Nuclear Information System (INIS)

    Zhou Jin; Chen Tianping; Xiang Lan

    2006-01-01

    This paper investigates synchronization dynamics of delayed neural networks with all the parameters unknown. By combining the adaptive control and linear feedback with the updated law, some simple yet generic criteria for determining the robust synchronization based on the parameters identification of uncertain chaotic delayed neural networks are derived by using the invariance principle of functional differential equations. It is shown that the approaches developed here further extend the ideas and techniques presented in recent literature, and they are also simple to implement in practice. Furthermore, the theoretical results are applied to a typical chaotic delayed Hopfied neural networks, and numerical simulation also demonstrate the effectiveness and feasibility of the proposed technique

  12. Robust fixed-time synchronization of delayed Cohen-Grossberg neural networks.

    Science.gov (United States)

    Wan, Ying; Cao, Jinde; Wen, Guanghui; Yu, Wenwu

    2016-01-01

    The fixed-time master-slave synchronization of Cohen-Grossberg neural networks with parameter uncertainties and time-varying delays is investigated. Compared with finite-time synchronization where the convergence time relies on the initial synchronization errors, the settling time of fixed-time synchronization can be adjusted to desired values regardless of initial conditions. Novel synchronization control strategy for the slave neural network is proposed. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, some sufficient schemes are provided for selecting the control parameters to ensure synchronization with required convergence time and in the presence of parameter uncertainties. Corresponding criteria for tuning control inputs are also derived for the finite-time synchronization. Finally, two numerical examples are given to illustrate the validity of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Structural damage detection robust against time synchronization errors

    International Nuclear Information System (INIS)

    Yan, Guirong; Dyke, Shirley J

    2010-01-01

    Structural damage detection based on wireless sensor networks can be affected significantly by time synchronization errors among sensors. Precise time synchronization of sensor nodes has been viewed as crucial for addressing this issue. However, precise time synchronization over a long period of time is often impractical in large wireless sensor networks due to two inherent challenges. First, time synchronization needs to be performed periodically, requiring frequent wireless communication among sensors at significant energy cost. Second, significant time synchronization errors may result from node failures which are likely to occur during long-term deployment over civil infrastructures. In this paper, a damage detection approach is proposed that is robust against time synchronization errors in wireless sensor networks. The paper first examines the ways in which time synchronization errors distort identified mode shapes, and then proposes a strategy for reducing distortion in the identified mode shapes. Modified values for these identified mode shapes are then used in conjunction with flexibility-based damage detection methods to localize damage. This alternative approach relaxes the need for frequent sensor synchronization and can tolerate significant time synchronization errors caused by node failures. The proposed approach is successfully demonstrated through numerical simulations and experimental tests in a lab

  14. Robustness of pinning a general complex dynamical network

    International Nuclear Information System (INIS)

    Wang Lei; Sun Youxian

    2010-01-01

    This Letter studies the robustness problem of pinning a general complex dynamical network toward an assigned synchronous evolution. Several synchronization criteria are presented to guarantee the convergence of the pinning process locally and globally by construction of Lyapunov functions. In particular, if a pinning strategy has been designed for synchronization of a given complex dynamical network, then no matter what uncertainties occur among the pinned nodes, synchronization can still be guaranteed through the pinning. The analytical results show that pinning control has a certain robustness against perturbations on network architecture: adding, deleting and changing the weights of edges. Numerical simulations illustrated by scale-free complex networks verify the theoretical results above-acquired.

  15. Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

    International Nuclear Information System (INIS)

    Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong

    2014-01-01

    All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations

  16. Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

    Science.gov (United States)

    Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong

    2014-06-01

    All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.

  17. Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Jianbao [School of Science, Hangzhou Dianzi University, Hangzhou 310018 (China); Ma, Zhongjun, E-mail: mzj1234402@163.com [School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004 (China); Chen, Guanrong [Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong (China)

    2014-06-15

    All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.

  18. Analysis of remote synchronization in complex networks

    Science.gov (United States)

    Gambuzza, Lucia Valentina; Cardillo, Alessio; Fiasconaro, Alessandro; Fortuna, Luigi; Gómez-Gardeñes, Jesus; Frasca, Mattia

    2013-12-01

    A novel regime of synchronization, called remote synchronization, where the peripheral nodes form a phase synchronized cluster not including the hub, was recently observed in star motifs [Bergner et al., Phys. Rev. E 85, 026208 (2012)]. We show the existence of a more general dynamical state of remote synchronization in arbitrary networks of coupled oscillators. This state is characterized by the synchronization of pairs of nodes that are not directly connected via a physical link or any sequence of synchronized nodes. This phenomenon is almost negligible in networks of phase oscillators as its underlying mechanism is the modulation of the amplitude of those intermediary nodes between the remotely synchronized units. Our findings thus show the ubiquity and robustness of these states and bridge the gap from their recent observation in simple toy graphs to complex networks.

  19. Robust synchronization control scheme of a population of nonlinear stochastic synthetic genetic oscillators under intrinsic and extrinsic molecular noise via quorum sensing.

    Science.gov (United States)

    Chen, Bor-Sen; Hsu, Chih-Yuan

    2012-10-26

    Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI

  20. Time-varying multiplex network: Intralayer and interlayer synchronization

    Science.gov (United States)

    Rakshit, Sarbendu; Majhi, Soumen; Bera, Bidesh K.; Sinha, Sudeshna; Ghosh, Dibakar

    2017-12-01

    A large class of engineered and natural systems, ranging from transportation networks to neuronal networks, are best represented by multiplex network architectures, namely a network composed of two or more different layers where the mutual interaction in each layer may differ from other layers. Here we consider a multiplex network where the intralayer coupling interactions are switched stochastically with a characteristic frequency. We explore the intralayer and interlayer synchronization of such a time-varying multiplex network. We find that the analytically derived necessary condition for intralayer and interlayer synchronization, obtained by the master stability function approach, is in excellent agreement with our numerical results. Interestingly, we clearly find that the higher frequency of switching links in the layers enhances both intralayer and interlayer synchrony, yielding larger windows of synchronization. Further, we quantify the resilience of synchronous states against random perturbations, using a global stability measure based on the concept of basin stability, and this reveals that intralayer coupling strength is most crucial for determining both intralayer and interlayer synchrony. Lastly, we investigate the robustness of interlayer synchronization against a progressive demultiplexing of the multiplex structure, and we find that for rapid switching of intralayer links, the interlayer synchronization persists even when a large number of interlayer nodes are disconnected.

  1. Pattern formation and firing synchronization in networks of map neurons

    International Nuclear Information System (INIS)

    Wang Qingyun; Duan Zhisheng; Huang Lin; Chen Guanrong; Lu Qishao

    2007-01-01

    Patterns and collective phenomena such as firing synchronization are studied in networks of nonhomogeneous oscillatory neurons and mixtures of oscillatory and excitable neurons, with dynamics of each neuron described by a two-dimensional (2D) Rulkov map neuron. It is shown that as the coupling strength is increased, typical patterns emerge spatially, which propagate through the networks in the form of beautiful target waves or parallel ones depending on the size of networks. Furthermore, we investigate the transitions of firing synchronization characterized by the rate of firing when the coupling strength is increased. It is found that there exists an intermediate coupling strength; firing synchronization is minimal simultaneously irrespective of the size of networks. For further increasing the coupling strength, synchronization is enhanced. Since noise is inevitable in real neurons, we also investigate the effects of white noise on firing synchronization for different networks. For the networks of oscillatory neurons, it is shown that firing synchronization decreases when the noise level increases. For the missed networks, firing synchronization is robust under the noise conditions considered in this paper. Results presented in this paper should prove to be valuable for understanding the properties of collective dynamics in real neuronal networks

  2. Communicating via robust synchronization of chaotic lasers

    International Nuclear Information System (INIS)

    Lopez-Gutierrez, R.M.; Posadas-Castillo, C.; Lopez-Mancilla, D.; Cruz-Hernandez, C.

    2009-01-01

    In this paper, the robust synchronization problem for coupled chaotic Nd:YAG lasers is addressed. We resort to complex systems theory to achieve chaos synchronization. Based on stability theory, it is shown that the state trajectories of the perturbed error synchronization are ultimately bounded, provided the unperturbed synchronization error system is exponentially stable, and some conditions on the bounds of the perturbation terms are satisfied. So that, encoding, transmission, and decoding in chaotic optical communications are presented. We analyze the transmission and recovery of encrypted information when parameter mismatches are considered. Computer simulations are provided to show the effectiveness of this robustness synchronization property, we present the encrypted transmission of image messages, and we show that, the transmitted image is faithfully recovered.

  3. Communicating via robust synchronization of chaotic lasers

    Energy Technology Data Exchange (ETDEWEB)

    Lopez-Gutierrez, R.M. [Engineering Faculty, Baja California Autonomous University (UABC), Km. 103 Carret. Tij-Ens., 22860 Ensenada, B.C. (Mexico); Posadas-Castillo, C. [Engineering Faculty, Baja California Autonomous University (UABC), Km. 103 Carret. Tij-Ens., 22860 Ensenada, B.C. (Mexico); FIME, Autonomous University of Nuevo Leon (UANL), Pedro de Alba, S.N., Cd. Universitaria, San Nicolas de los Garza, NL (Mexico); Lopez-Mancilla, D. [Departamento de Ciencias Exactas y Tecnologicas, Centro Universitario de los Lagos, Universidad de Guadalajara (CULagos-UdeG), Enrique Diaz de Leon s/n, 47460 Lagos de Moreno, Jal. (Mexico); Cruz-Hernandez, C. [Electronics and Telecommunications Department, Scientific Research and Advanced Studies of Ensenada (CICESE), Km. 107 Carret. Tij-Ens., 22860 Ensenada, B.C. (Mexico)], E-mail: ccruz@cicese.mx

    2009-10-15

    In this paper, the robust synchronization problem for coupled chaotic Nd:YAG lasers is addressed. We resort to complex systems theory to achieve chaos synchronization. Based on stability theory, it is shown that the state trajectories of the perturbed error synchronization are ultimately bounded, provided the unperturbed synchronization error system is exponentially stable, and some conditions on the bounds of the perturbation terms are satisfied. So that, encoding, transmission, and decoding in chaotic optical communications are presented. We analyze the transmission and recovery of encrypted information when parameter mismatches are considered. Computer simulations are provided to show the effectiveness of this robustness synchronization property, we present the encrypted transmission of image messages, and we show that, the transmitted image is faithfully recovered.

  4. Protecting Clock Synchronization: Adversary Detection through Network Monitoring

    Directory of Open Access Journals (Sweden)

    Elena Lisova

    2016-01-01

    Full Text Available Nowadays, industrial networks are often used for safety-critical applications with real-time requirements. Such applications usually have a time-triggered nature with message scheduling as a core property. Scheduling requires nodes to share the same notion of time, that is, to be synchronized. Therefore, clock synchronization is a fundamental asset in real-time networks. However, since typical standards for clock synchronization, for example, IEEE 1588, do not provide the required level of security, it raises the question of clock synchronization protection. In this paper, we identify a way to break synchronization based on the IEEE 1588 standard, by conducting a man-in-the-middle (MIM attack followed by a delay attack. A MIM attack can be accomplished through, for example, Address Resolution Protocol (ARP poisoning. Using the AVISPA tool, we evaluate the potential to perform a delay attack using ARP poisoning and analyze its consequences showing both that the attack can, indeed, break clock synchronization and that some design choices, such as a relaxed synchronization condition mode, delay bounding, and using knowledge of environmental conditions, can make the network more robust/resilient against these kinds of attacks. Lastly, a Configuration Agent is proposed to monitor and detect anomalies introduced by an adversary performing attacks targeting clock synchronization.

  5. A Robust Synchronization to Enhance the Power Quality of Renewable Energy Systems

    DEFF Research Database (Denmark)

    Hadjidemetriou, Lenos; Kyriakides, Elias; Blaabjerg, Frede

    2015-01-01

    The increasing penetration of renewable energy sources (RESs) in the power grid requires high-quality power injection under various grid conditions. The synchronization method, usually a phase-locked loop (PLL) algorithm, is directly affecting the response of the grid-side converter of the RES....... This paper proposes a new PLL algorithm that uses an advanced decoupling network implemented in the stationary reference frame with limited requirements for processing time to enable a fast and accurate synchronization even under harmonic distorted voltage and low-voltage grid faults. The robust response...... of the proposed PLL is validated, and the effect of the proposed synchronization on the performance of the grid-connected renewable energy system is investigated. This investigation proves that the robust, accurate, and dynamic response of the new PLL can enhance the quality of the injected power from the RES...

  6. Enhanced robust fractional order proportional-plus-integral controller based on neural network for velocity control of permanent magnet synchronous motor.

    Science.gov (United States)

    Zhang, Bitao; Pi, YouGuo

    2013-07-01

    The traditional integer order proportional-integral-differential (IO-PID) controller is sensitive to the parameter variation or/and external load disturbance of permanent magnet synchronous motor (PMSM). And the fractional order proportional-integral-differential (FO-PID) control scheme based on robustness tuning method is proposed to enhance the robustness. But the robustness focuses on the open-loop gain variation of controlled plant. In this paper, an enhanced robust fractional order proportional-plus-integral (ERFOPI) controller based on neural network is proposed. The control law of the ERFOPI controller is acted on a fractional order implement function (FOIF) of tracking error but not tracking error directly, which, according to theory analysis, can enhance the robust performance of system. Tuning rules and approaches, based on phase margin, crossover frequency specification and robustness rejecting gain variation, are introduced to obtain the parameters of ERFOPI controller. And the neural network algorithm is used to adjust the parameter of FOIF. Simulation and experimental results show that the method proposed in this paper not only achieve favorable tracking performance, but also is robust with regard to external load disturbance and parameter variation. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  7. Synchronization on effective networks

    International Nuclear Information System (INIS)

    Zhou Tao; Zhao Ming; Zhou Changsong

    2010-01-01

    The study of network synchronization has attracted increasing attentionrecently. In this paper, we strictly define a class of networks, namely effective networks, which are synchronizable and orientable networks. We can prove that all the effective networks with the same size have the same spectra, and are of the best synchronizability according to the master stability analysis. However, it is found that the synchronization time for different effective networks can be quite different. Further analysis shows that the key ingredient affecting the synchronization time is the maximal depth of an effective network: the larger depth results in a longer synchronization time. The secondary factor is the number of links. The increasing number of links connecting nodes in the same layer (horizontal links) will lead to longer synchronization time, whereas the increasing number of links connecting nodes in neighboring layers (vertical links) will accelerate the synchronization. Our analysis of the relationship between the structure and synchronization properties of the original and effective networks shows that the purely directed effective network can provide an approximation of the original weighted network with normalized input strength. Our findings provide insights into the roles of depth, horizontal and vertical links in the synchronizing process, and suggest that the spectral analysis is helpful yet insufficient for the comprehensive understanding of network synchronization.

  8. Synchronization on effective networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Tao [Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 610054 (China); Zhao Ming [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China); Zhou Changsong, E-mail: cszhou@hkbu.edu.h [Department of Physics, Hong Kong Baptist University, Kowloon Tong (Hong Kong)

    2010-04-15

    The study of network synchronization has attracted increasing attentionrecently. In this paper, we strictly define a class of networks, namely effective networks, which are synchronizable and orientable networks. We can prove that all the effective networks with the same size have the same spectra, and are of the best synchronizability according to the master stability analysis. However, it is found that the synchronization time for different effective networks can be quite different. Further analysis shows that the key ingredient affecting the synchronization time is the maximal depth of an effective network: the larger depth results in a longer synchronization time. The secondary factor is the number of links. The increasing number of links connecting nodes in the same layer (horizontal links) will lead to longer synchronization time, whereas the increasing number of links connecting nodes in neighboring layers (vertical links) will accelerate the synchronization. Our analysis of the relationship between the structure and synchronization properties of the original and effective networks shows that the purely directed effective network can provide an approximation of the original weighted network with normalized input strength. Our findings provide insights into the roles of depth, horizontal and vertical links in the synchronizing process, and suggest that the spectral analysis is helpful yet insufficient for the comprehensive understanding of network synchronization.

  9. Robust fixed-time synchronization for uncertain complex-valued neural networks with discontinuous activation functions.

    Science.gov (United States)

    Ding, Xiaoshuai; Cao, Jinde; Alsaedi, Ahmed; Alsaadi, Fuad E; Hayat, Tasawar

    2017-06-01

    This paper is concerned with the fixed-time synchronization for a class of complex-valued neural networks in the presence of discontinuous activation functions and parameter uncertainties. Fixed-time synchronization not only claims that the considered master-slave system realizes synchronization within a finite time segment, but also requires a uniform upper bound for such time intervals for all initial synchronization errors. To accomplish the target of fixed-time synchronization, a novel feedback control procedure is designed for the slave neural networks. By means of the Filippov discontinuity theories and Lyapunov stability theories, some sufficient conditions are established for the selection of control parameters to guarantee synchronization within a fixed time, while an upper bound of the settling time is acquired as well, which allows to be modulated to predefined values independently on initial conditions. Additionally, criteria of modified controller for assurance of fixed-time anti-synchronization are also derived for the same system. An example is included to illustrate the proposed methodologies. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Robust Timing Synchronization in Aeronautical Mobile Communication Systems

    Science.gov (United States)

    Xiong, Fu-Qin; Pinchak, Stanley

    2004-01-01

    This work details a study of robust synchronization schemes suitable for satellite to mobile aeronautical applications. A new scheme, the Modified Sliding Window Synchronizer (MSWS), is devised and compared with existing schemes, including the traditional Early-Late Gate Synchronizer (ELGS), the Gardner Zero-Crossing Detector (GZCD), and the Sliding Window Synchronizer (SWS). Performance of the synchronization schemes is evaluated by a set of metrics that indicate performance in digital communications systems. The metrics are convergence time, mean square phase error (or root mean-square phase error), lowest SNR for locking, initial frequency offset performance, midstream frequency offset performance, and system complexity. The performance of the synchronizers is evaluated by means of Matlab simulation models. A simulation platform is devised to model the satellite to mobile aeronautical channel, consisting of a Quadrature Phase Shift Keying modulator, an additive white Gaussian noise channel, and a demodulator front end. Simulation results show that the MSWS provides the most robust performance at the cost of system complexity. The GZCD provides a good tradeoff between robustness and system complexity for communication systems that require high symbol rates or low overall system costs. The ELGS has a high system complexity despite its average performance. Overall, the SWS, originally designed for multi-carrier systems, performs very poorly in single-carrier communications systems. Table 5.1 in Section 5 provides a ranking of each of the synchronization schemes in terms of the metrics set forth in Section 4.1. Details of comparison are given in Section 5. Based on the results presented in Table 5, it is safe to say that the most robust synchronization scheme examined in this work is the high-sample-rate Modified Sliding Window Synchronizer. A close second is its low-sample-rate cousin. The tradeoff between complexity and lowest mean-square phase error determines

  11. Robust tracking and distributed synchronization control of a multi-motor servomechanism with H-infinity performance.

    Science.gov (United States)

    Wang, Minlin; Ren, Xuemei; Chen, Qiang

    2018-01-01

    The multi-motor servomechanism (MMS) is a multi-variable, high coupling and nonlinear system, which makes the controller design challenging. In this paper, an adaptive robust H-infinity control scheme is proposed to achieve both the load tracking and multi-motor synchronization of MMS. This control scheme consists of two parts: a robust tracking controller and a distributed synchronization controller. The robust tracking controller is constructed by incorporating a neural network (NN) K-filter observer into the dynamic surface control, while the distributed synchronization controller is designed by combining the mean deviation coupling control strategy with the distributed technique. The proposed control scheme has several merits: 1) by using the mean deviation coupling synchronization control strategy, the tracking controller and the synchronization controller can be designed individually without any coupling problem; 2) the immeasurable states and unknown nonlinearities are handled by a NN K-filter observer, where the number of NN weights is largely reduced by using the minimal learning parameter technique; 3) the H-infinity performances of tracking error and synchronization error are guaranteed by introducing a robust term into the tracking controller and the synchronization controller, respectively. The stabilities of the tracking and synchronization control systems are analyzed by the Lyapunov theory. Simulation and experimental results based on a four-motor servomechanism are conducted to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Robust Adaptive Synchronization of Ring Configured Uncertain Chaotic FitzHugh–Nagumo Neurons under Direction-Dependent Coupling

    Directory of Open Access Journals (Sweden)

    Muhammad Iqbal

    2018-02-01

    Full Text Available This paper exploits the dynamical modeling, behavior analysis, and synchronization of a network of four different FitzHugh–Nagumo (FHN neurons with unknown parameters linked in a ring configuration under direction-dependent coupling. The main purpose is to investigate a robust adaptive control law for the synchronization of uncertain and perturbed neurons, communicating in a medium of bidirectional coupling. The neurons are assumed to be different and interconnected in a ring structure. The strength of the gap junctions is taken to be different for each link in the network, owing to the inter-neuronal coupling medium properties. Robust adaptive control mechanism based on Lyapunov stability analysis is employed and theoretical criteria are derived to realize the synchronization of the network of four FHN neurons in a ring form with unknown parameters under direction-dependent coupling and disturbances. The proposed scheme for synchronization of dissimilar neurons, under external electrical stimuli, coupled in a ring communication topology, having all parameters unknown, and subject to directional coupling medium and perturbations, is addressed for the first time as per our knowledge. To demonstrate the efficacy of the proposed strategy, simulation results are provided.

  13. Robust Adaptive Synchronization of Ring Configured Uncertain Chaotic FitzHugh–Nagumo Neurons under Direction-Dependent Coupling

    Science.gov (United States)

    Iqbal, Muhammad; Rehan, Muhammad; Hong, Keum-Shik

    2018-01-01

    This paper exploits the dynamical modeling, behavior analysis, and synchronization of a network of four different FitzHugh–Nagumo (FHN) neurons with unknown parameters linked in a ring configuration under direction-dependent coupling. The main purpose is to investigate a robust adaptive control law for the synchronization of uncertain and perturbed neurons, communicating in a medium of bidirectional coupling. The neurons are assumed to be different and interconnected in a ring structure. The strength of the gap junctions is taken to be different for each link in the network, owing to the inter-neuronal coupling medium properties. Robust adaptive control mechanism based on Lyapunov stability analysis is employed and theoretical criteria are derived to realize the synchronization of the network of four FHN neurons in a ring form with unknown parameters under direction-dependent coupling and disturbances. The proposed scheme for synchronization of dissimilar neurons, under external electrical stimuli, coupled in a ring communication topology, having all parameters unknown, and subject to directional coupling medium and perturbations, is addressed for the first time as per our knowledge. To demonstrate the efficacy of the proposed strategy, simulation results are provided. PMID:29535622

  14. Synchronization in a non-uniform network of excitatory spiking neurons

    Science.gov (United States)

    Echeveste, Rodrigo; Gros, Claudius

    Spontaneous synchronization of pulse coupled elements is ubiquitous in nature and seems to be of vital importance for life. Networks of pacemaker cells in the heart, extended populations of southeast asian fireflies, and neuronal oscillations in cortical networks, are examples of this. In the present work, a rich repertoire of dynamical states with different degrees of synchronization are found in a network of excitatory-only spiking neurons connected in a non-uniform fashion. In particular, uncorrelated and partially correlated states are found without the need for inhibitory neurons or external currents. The phase transitions between these states, as well the robustness, stability, and response of the network to external stimulus are studied.

  15. Space Network Time Distribution and Synchronization Protocol Development for Mars Proximity Link

    Science.gov (United States)

    Woo, Simon S.; Gao, Jay L.; Mills, David

    2010-01-01

    Time distribution and synchronization in deep space network are challenging due to long propagation delays, spacecraft movements, and relativistic effects. Further, the Network Time Protocol (NTP) designed for terrestrial networks may not work properly in space. In this work, we consider the time distribution protocol based on time message exchanges similar to Network Time Protocol (NTP). We present the Proximity-1 Space Link Interleaved Time Synchronization (PITS) algorithm that can work with the CCSDS Proximity-1 Space Data Link Protocol. The PITS algorithm provides faster time synchronization via two-way time transfer over proximity links, improves scalability as the number of spacecraft increase, lowers storage space requirement for collecting time samples, and is robust against packet loss and duplication which underlying protocol mechanisms provide.

  16. Robust emergence of small-world structure in networks of spiking neurons.

    Science.gov (United States)

    Kwok, Hoi Fei; Jurica, Peter; Raffone, Antonino; van Leeuwen, Cees

    2007-03-01

    Spontaneous activity in biological neural networks shows patterns of dynamic synchronization. We propose that these patterns support the formation of a small-world structure-network connectivity optimal for distributed information processing. We present numerical simulations with connected Hindmarsh-Rose neurons in which, starting from random connection distributions, small-world networks evolve as a result of applying an adaptive rewiring rule. The rule connects pairs of neurons that tend fire in synchrony, and disconnects ones that fail to synchronize. Repeated application of the rule leads to small-world structures. This mechanism is robustly observed for bursting and irregular firing regimes.

  17. Pinning Synchronization of Switched Complex Dynamical Networks

    Directory of Open Access Journals (Sweden)

    Liming Du

    2015-01-01

    Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.

  18. Robust fault-sensitive synchronization of a class of nonlinear systems

    International Nuclear Information System (INIS)

    Xu Shi-Yun; Tang Yong; Sun Hua-Dong; Yang Ying; Liu Xian

    2011-01-01

    Aiming at enhancing the quality as well as the reliability of synchronization, this paper is concerned with the fault detection issue within the synchronization process for a class of nonlinear systems in the existence of external disturbances. To handle such problems, the concept of robust fault-sensitive (RFS) synchronization is proposed, and a method of determining such a kind of synchronization is developed. Under the framework of RFS synchronization, the master and the slave systems are robustly synchronized, and at the same time, sensitive to possible faults based on a mixed H − /H ∞ performance. The design of desired output feedback controller is realized by solving a linear matrix inequality, and the fault sensitivity H − index can be optimized via a convex optimization algorithm. A master-slave configuration composed of identical Chua's circuits is adopted as a numerical example to demonstrate the effectiveness and applicability of the analytical results. (general)

  19. Pinning-controlled synchronization of complex networks with bounded or unbounded synchronized regions

    International Nuclear Information System (INIS)

    Yan-Li, Zou; Guan-Rong, Chen

    2009-01-01

    This paper studies pinning-controlled synchronization of complex networks with bounded or unbounded synchronized regions. To study a state-feedback pinning-controlled network with N nodes, it first converts the controlled network to an extended network of N+1 nodes without controls. It is shown that the controlled synchronizability of the given network is determined by the real part of the smallest nonzero eigenvalue of the coupling matrix of its extended network when the synchronized region is unbounded; but it is determined by the ratio of the real parts of the largest and the smallest nonzero eigenvalues of the coupling matrix when the synchronized region is bounded. Both theoretical analysis and numerical simulation show that the portion of controlled nodes has no critical values when the synchronized region is unbounded, but it has a critical value when the synchronized region is bounded. In the former case, therefore, it is possible to control the network to achieve synchronization by pinning only one node. In the latter case, the network can achieve controlled synchronization only when the portion of controlled nodes is larger than the critical value. (general)

  20. Synchronization in complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Arenas, A.; Diaz-Guilera, A.; Moreno, Y.; Zhou, C.; Kurths, J.

    2007-12-12

    Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.

  1. Synchronous ethernet and IEEE 1588 in telecoms next generation synchronization networks

    CERN Document Server

    2013-01-01

    This book addresses the multiple technical aspects of the distribution of synchronization in new generation telecommunication networks, focusing in particular on synchronous Ethernet and IEEE1588 technologies. Many packet network engineers struggle with understanding the challenges that precise synchronization distribution can impose on networks. The usual “why”, “when” and particularly “how” can cause problems for many engineers. In parallel to this, some other markets have identical synchronization requirements, but with their own design requirements, generating further questions. This book attempts to respond to the different questions by providing background technical information. Invaluable information on state of-the-art packet network synchronization and timing architectures is provided, as well as an unbiased view on the synchronization technologies that have been internationally standardized over recent years, with the aim of providing the average reader (who is not skilled in the art) wi...

  2. Outer Synchronization of Complex Networks by Impulse

    International Nuclear Information System (INIS)

    Sun Wen; Yan Zizong; Chen Shihua; Lü Jinhu

    2011-01-01

    This paper investigates outer synchronization of complex networks, especially, outer complete synchronization and outer anti-synchronization between the driving network and the response network. Employing the impulsive control method which is uncontinuous, simple, efficient, low-cost and easy to implement in practical applications, we obtain some sufficient conditions of outer complete synchronization and outer anti-synchronization between two complex networks. Numerical simulations demonstrate the effectiveness of the proposed impulsive control scheme. (general)

  3. Synchronization of networks

    Indian Academy of Sciences (India)

    We study the synchronization of coupled dynamical systems on networks. The dynamics is .... Such a time-varying topology can occur in social networks, computer networks, WWW ... This has the effect of reducing the spread of the transverse ...

  4. Re-verification of a Lip Synchronization Protocol using Robust Reachability

    Directory of Open Access Journals (Sweden)

    Piotr Kordy

    2010-03-01

    Full Text Available The timed automata formalism is an important model for specifying and analysing real-time systems. Robustness is the correctness of the model in the presence of small drifts on clocks or imprecision in testing guards. A symbolic algorithm for the analysis of the robustness of timed automata has been implemented. In this paper, we re-analyse an industrial case lip synchronization protocol using the new robust reachability algorithm. This lip synchronization protocol is an interesting case because timing aspects are crucial for the correctness of the protocol. Several versions of the model are considered: with an ideal video stream, with anchored jitter, and with non-anchored jitter.

  5. Robust finite-time chaos synchronization of uncertain permanent magnet synchronous motors.

    Science.gov (United States)

    Chen, Qiang; Ren, Xuemei; Na, Jing

    2015-09-01

    In this paper, a robust finite-time chaos synchronization scheme is proposed for two uncertain third-order permanent magnet synchronous motors (PMSMs). The whole synchronization error system is divided into two cascaded subsystems: a first-order subsystem and a second-order subsystem. For the first subsystem, we design a finite-time controller based on the finite-time Lyapunov stability theory. Then, according to the backstepping idea and the adding a power integrator technique, a second finite-time controller is constructed recursively for the second subsystem. No exogenous forces are required in the controllers design but only the direct-axis (d-axis) and the quadrature-axis (q-axis) stator voltages are used as manipulated variables. Comparative simulations are provided to show the effectiveness and superior performance of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Fitness for synchronization of network motifs

    DEFF Research Database (Denmark)

    Vega, Y.M.; Vázquez-Prada, M.; Pacheco, A.F.

    2004-01-01

    We study the synchronization of Kuramoto's oscillators in small parts of networks known as motifs. We first report on the system dynamics for the case of a scale-free network and show the existence of a non-trivial critical point. We compute the probability that network motifs synchronize, and fi...... that the fitness for synchronization correlates well with motifs interconnectedness and structural complexity. Possible implications for present debates about network evolution in biological and other systems are discussed....

  7. Synchronization in complex networks with a modular structure.

    Science.gov (United States)

    Park, Kwangho; Lai, Ying-Cheng; Gupte, Saurabh; Kim, Jong-Won

    2006-03-01

    Networks with a community (or modular) structure arise in social and biological sciences. In such a network individuals tend to form local communities, each having dense internal connections. The linkage among the communities is, however, much more sparse. The dynamics on modular networks, for instance synchronization, may be of great social or biological interest. (Here by synchronization we mean some synchronous behavior among the nodes in the network, not, for example, partially synchronous behavior in the network or the synchronizability of the network with some external dynamics.) By using a recent theoretical framework, the master-stability approach originally introduced by Pecora and Carroll in the context of synchronization in coupled nonlinear oscillators, we address synchronization in complex modular networks. We use a prototype model and develop scaling relations for the network synchronizability with respect to variations of some key network structural parameters. Our results indicate that random, long-range links among distant modules is the key to synchronization. As an application we suggest a viable strategy to achieve synchronous behavior in social networks.

  8. Robust Synchronization of Delayed Chaotic FitzHugh-Nagumo Neurons under External Electrical Stimulation

    Directory of Open Access Journals (Sweden)

    Muhammad Rehan

    2012-01-01

    Full Text Available Synchronization of chaotic neurons under external electrical stimulation (EES is studied in order to understand information processing in the brain and to improve the methodologies employed in the treatment of cognitive diseases. This paper investigates the dynamics of uncertain coupled chaotic delayed FitzHugh-Nagumo (FHN neurons under EES for incorporated parametric variations. A global nonlinear control law for synchronization of delayed neurons with known parameters is developed. Based on local and global Lipschitz conditions, knowledge of the bounds on the neuronal states, the Lyapunov-Krasovskii functional, and the L2 gain reduction, a less conservative local robust nonlinear control law is formulated to address the problem of robust asymptotic synchronization of delayed FHN neurons under parametric uncertainties. The proposed local control law guarantees both robust stability and robust performance and provides the L2 bound for uncertainty rejection in the synchronization error dynamics. Separate conditions for single-input and multiple-input control schemes for synchronization of a wide class of FHN systems are provided. The results of the proposed techniques are verified through numerical simulations.

  9. Synchronization of networks

    Indian Academy of Sciences (India)

    We study the synchronization of coupled dynamical systems on networks. The dynamics is governed by a local nonlinear oscillator for each node of the network and interactions connecting different nodes via the links of the network. We consider existence and stability conditions for both single- and multi-cluster ...

  10. Synchronization in complex networks with switching topology

    International Nuclear Information System (INIS)

    Wang, Lei; Wang, Qing-guo

    2011-01-01

    This Letter investigates synchronization issues of complex dynamical networks with switching topology. By constructing a common Lyapunov function, we show that local and global synchronization for a linearly coupled network with switching topology can be evaluated by the time average of second smallest eigenvalues corresponding to the Laplacians of switching topology. This result is quite powerful and can be further used to explore various switching cases for complex dynamical networks. Numerical simulations illustrate the effectiveness of the obtained results in the end. -- Highlights: → Synchronization of complex networks with switching topology is investigated. → A common Lyapunov function is established for synchronization of switching network. → The common Lyapunov function is not necessary to monotonically decrease with time. → Synchronization is determined by the second smallest eigenvalue of its Laplacian. → Synchronization criterion can be used to investigate various switching cases.

  11. Adaptive Synchronization of Robotic Sensor Networks

    OpenAIRE

    Yıldırım, Kasım Sinan; Gürcan, Önder

    2014-01-01

    The main focus of recent time synchronization research is developing power-efficient synchronization methods that meet pre-defined accuracy requirements. However, an aspect that has been often overlooked is the high dynamics of the network topology due to the mobility of the nodes. Employing existing flooding-based and peer-to-peer synchronization methods, are networked robots still be able to adapt themselves and self-adjust their logical clocks under mobile network dynamics? In this paper, ...

  12. Bursting synchronization in clustered neuronal networks

    International Nuclear Information System (INIS)

    Yu Hai-Tao; Wang Jiang; Deng Bin; Wei Xi-Le

    2013-01-01

    Neuronal networks in the brain exhibit the modular (clustered) property, i.e., they are composed of certain subnetworks with differential internal and external connectivity. We investigate bursting synchronization in a clustered neuronal network. A transition to mutual-phase synchronization takes place on the bursting time scale of coupled neurons, while on the spiking time scale, they behave asynchronously. This synchronization transition can be induced by the variations of inter- and intracoupling strengths, as well as the probability of random links between different subnetworks. Considering that some pathological conditions are related with the synchronization of bursting neurons in the brain, we analyze the control of bursting synchronization by using a time-periodic external signal in the clustered neuronal network. Simulation results show a frequency locking tongue in the driving parameter plane, where bursting synchronization is maintained, even in the presence of external driving. Hence, effective synchronization suppression can be realized with the driving parameters outside the frequency locking region. (interdisciplinary physics and related areas of science and technology)

  13. Synchronization in complex networks with adaptive coupling

    International Nuclear Information System (INIS)

    Zhang Rong; Hu Manfeng; Xu Zhenyuan

    2007-01-01

    Generally it is very difficult to realized synchronization for some complex networks. In order to synchronize, the coupling coefficient of networks has to be very large, especially when the number of coupled nodes is larger. In this Letter, we consider the problem of synchronization in complex networks with adaptive coupling. A new concept about asymptotic stability is presented, then we proved by using the well-known LaSalle invariance principle, that the state of such a complex network can synchronize an arbitrary assigned state of an isolated node of the network as long as the feedback gain is positive. Unified system is simulated as the nodes of adaptive coupling complex networks with different topologies

  14. Synchronization in networks with heterogeneous coupling delays

    Science.gov (United States)

    Otto, Andreas; Radons, Günter; Bachrathy, Dániel; Orosz, Gábor

    2018-01-01

    Synchronization in networks of identical oscillators with heterogeneous coupling delays is studied. A decomposition of the network dynamics is obtained by block diagonalizing a newly introduced adjacency lag operator which contains the topology of the network as well as the corresponding coupling delays. This generalizes the master stability function approach, which was developed for homogenous delays. As a result the network dynamics can be analyzed by delay differential equations with distributed delay, where different delay distributions emerge for different network modes. Frequency domain methods are used for the stability analysis of synchronized equilibria and synchronized periodic orbits. As an example, the synchronization behavior in a system of delay-coupled Hodgkin-Huxley neurons is investigated. It is shown that the parameter regions where synchronized periodic spiking is unstable expand when increasing the delay heterogeneity.

  15. Modeling and simulation of permanent magnet synchronous motor based on neural network control strategy

    Science.gov (United States)

    Luo, Bingyang; Chi, Shangjie; Fang, Man; Li, Mengchao

    2017-03-01

    Permanent magnet synchronous motor is used widely in industry, the performance requirements wouldn't be met by adopting traditional PID control in some of the occasions with high requirements. In this paper, a hybrid control strategy - nonlinear neural network PID and traditional PID parallel control are adopted. The high stability and reliability of traditional PID was combined with the strong adaptive ability and robustness of neural network. The permanent magnet synchronous motor will get better control performance when switch different working modes according to different controlled object conditions. As the results showed, the speed response adopting the composite control strategy in this paper was faster than the single control strategy. And in the case of sudden disturbance, the recovery time adopting the composite control strategy designed in this paper was shorter, the recovery ability and the robustness were stronger.

  16. Simulating synchronization in neuronal networks

    Science.gov (United States)

    Fink, Christian G.

    2016-06-01

    We discuss several techniques used in simulating neuronal networks by exploring how a network's connectivity structure affects its propensity for synchronous spiking. Network connectivity is generated using the Watts-Strogatz small-world algorithm, and two key measures of network structure are described. These measures quantify structural characteristics that influence collective neuronal spiking, which is simulated using the leaky integrate-and-fire model. Simulations show that adding a small number of random connections to an otherwise lattice-like connectivity structure leads to a dramatic increase in neuronal synchronization.

  17. Impulsive generalized function synchronization of complex dynamical networks

    International Nuclear Information System (INIS)

    Zhang, Qunjiao; Chen, Juan; Wan, Li

    2013-01-01

    This Letter investigates generalized function synchronization of continuous and discrete complex networks by impulsive control. By constructing the reasonable corresponding impulsively controlled response networks, some criteria and corollaries are derived for the generalized function synchronization between the impulsively controlled complex networks, continuous and discrete networks are both included. Furthermore, the generalized linear synchronization and nonlinear synchronization are respectively illustrated by several examples. All the numerical simulations demonstrate the correctness of the theoretical results

  18. Computer network time synchronization the network time protocol

    CERN Document Server

    Mills, David L

    2006-01-01

    What started with the sundial has, thus far, been refined to a level of precision based on atomic resonance: Time. Our obsession with time is evident in this continued scaling down to nanosecond resolution and beyond. But this obsession is not without warrant. Precision and time synchronization are critical in many applications, such as air traffic control and stock trading, and pose complex and important challenges in modern information networks.Penned by David L. Mills, the original developer of the Network Time Protocol (NTP), Computer Network Time Synchronization: The Network Time Protocol

  19. Emergent explosive synchronization in adaptive complex networks

    Science.gov (United States)

    Avalos-Gaytán, Vanesa; Almendral, Juan A.; Leyva, I.; Battiston, F.; Nicosia, V.; Latora, V.; Boccaletti, S.

    2018-04-01

    Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

  20. Synchronous bursts on scale-free neuronal networks with attractive and repulsive coupling.

    Directory of Open Access Journals (Sweden)

    Qingyun Wang

    Full Text Available This paper investigates the dependence of synchronization transitions of bursting oscillations on the information transmission delay over scale-free neuronal networks with attractive and repulsive coupling. It is shown that for both types of coupling, the delay always plays a subtle role in either promoting or impairing synchronization. In particular, depending on the inherent oscillation period of individual neurons, regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases. These delay-induced synchronization transitions are manifested as well-expressed minima in the measure for spatiotemporal synchrony. For attractive coupling, the minima appear at every integer multiple of the average oscillation period, while for the repulsive coupling, they appear at every odd multiple of the half of the average oscillation period. The obtained results are robust to the variations of the dynamics of individual neurons, the system size, and the neuronal firing type. Hence, they can be used to characterize attractively or repulsively coupled scale-free neuronal networks with delays.

  1. Explosive synchronization transitions in complex neural networks

    Science.gov (United States)

    Chen, Hanshuang; He, Gang; Huang, Feng; Shen, Chuansheng; Hou, Zhonghuai

    2013-09-01

    It has been recently reported that explosive synchronization transitions can take place in networks of phase oscillators [Gómez-Gardeñes et al. Phys. Rev. Lett. 106, 128701 (2011)] and chaotic oscillators [Leyva et al. Phys. Rev. Lett. 108, 168702 (2012)]. Here, we investigate the effect of a microscopic correlation between the dynamics and the interacting topology of coupled FitzHugh-Nagumo oscillators on phase synchronization transition in Barabási-Albert (BA) scale-free networks and Erdös-Rényi (ER) random networks. We show that, if natural frequencies of the oscillations are positively correlated with node degrees and the width of the frequency distribution is larger than a threshold value, a strong hysteresis loop arises in the synchronization diagram of BA networks, indicating the evidence of an explosive transition towards synchronization of relaxation oscillators system. In contrast to the results in BA networks, in more homogeneous ER networks, the synchronization transition is always of continuous type regardless of the width of the frequency distribution. Moreover, we consider the effect of degree-mixing patterns on the nature of the synchronization transition, and find that the degree assortativity is unfavorable for the occurrence of such an explosive transition.

  2. On synchronized regions of discrete-time complex dynamical networks

    International Nuclear Information System (INIS)

    Duan Zhisheng; Chen Guanrong

    2011-01-01

    In this paper, the local synchronization of discrete-time complex networks is studied. First, it is shown that for any natural number n, there exists a discrete-time network which has at least left floor n/2 right floor +1 disconnected synchronized regions for local synchronization, which implies the possibility of intermittent synchronization behaviors. Different from the continuous-time networks, the existence of an unbounded synchronized region is impossible for discrete-time networks. The convexity of the synchronized regions is also characterized based on the stability of a class of matrix pencils, which is useful for enlarging the stability region so as to improve the network synchronizability.

  3. Synchronization of oscillators in complex networks

    Indian Academy of Sciences (India)

    Abstract. Theory of identical or complete synchronization of identical oscillators in arbitrary networks is introduced. In addition, several graph theory concepts and results that augment the synchronization theory and a tie in closely to random, semirandom, and regular networks are introduced. Combined theories are used to ...

  4. Synchronization of oscillators in complex networks

    Indian Academy of Sciences (India)

    Theory of identical or complete synchronization of identical oscillators in arbitrary networks is introduced. In addition, several graph theory concepts and results that augment the synchronization theory and a tie in closely to random, semirandom, and regular networks are introduced. Combined theories are used to explore ...

  5. Multicellular models of intercellular synchronization in circadian neural networks

    International Nuclear Information System (INIS)

    Henson, Michael A.

    2013-01-01

    The circadian clock generates 24 h rhythms that drive physiological and behavioral processes in a diverse range of organisms including microbes, plants, insects, and mammals. Recent experimental advances have produced improved understanding of the molecular mechanisms involved in circadian rhythm generation at the single cell level. However, the intercellular mechanisms that allow large populations of coupled pacemaker cells to synchronize and coordinate their rhythms remain poorly understood. The purpose of this article is to review recent progress in dynamic modeling of the circadian clock with a focus on multicellular models required to describe cell population synchronization. Mammalian systems are emphasized to illustrate the highly heterogeneous structure and rich dynamical behavior of multicellular circadian systems. Available multicellular models are characterized with respect to their single cell descriptions, intercellular coupling mechanisms, and network topologies. Examples drawn from our own research are used to demonstrate the advantages associated with integrating detailed single cell models within realistic multicellular networks for prediction of mammalian system dynamics. Mathematical modeling is shown to represent a powerful tool for understanding the intracellular and intercellular mechanisms utilized to robustly synchronize large populations of highly heterogeneous and sparsely coupled single cell oscillators. The article concludes with some possible directions for future research

  6. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

    Science.gov (United States)

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustnessnetwork robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

  7. Intermittent synchronization in a network of bursting neurons

    Science.gov (United States)

    Park, Choongseok; Rubchinsky, Leonid L.

    2011-09-01

    Synchronized oscillations in networks of inhibitory and excitatory coupled bursting neurons are common in a variety of neural systems from central pattern generators to human brain circuits. One example of the latter is the subcortical network of the basal ganglia, formed by excitatory and inhibitory bursters of the subthalamic nucleus and globus pallidus, involved in motor control and affected in Parkinson's disease. Recent experiments have demonstrated the intermittent nature of the phase-locking of neural activity in this network. Here, we explore one potential mechanism to explain the intermittent phase-locking in a network. We simplify the network to obtain a model of two inhibitory coupled elements and explore its dynamics. We used geometric analysis and singular perturbation methods for dynamical systems to reduce the full model to a simpler set of equations. Mathematical analysis was completed using three slow variables with two different time scales. Intermittently, synchronous oscillations are generated by overlapped spiking which crucially depends on the geometry of the slow phase plane and the interplay between slow variables as well as the strength of synapses. Two slow variables are responsible for the generation of activity patterns with overlapped spiking, and the other slower variable enhances the robustness of an irregular and intermittent activity pattern. While the analyzed network and the explored mechanism of intermittent synchrony appear to be quite generic, the results of this analysis can be used to trace particular values of biophysical parameters (synaptic strength and parameters of calcium dynamics), which are known to be impacted in Parkinson's disease.

  8. Synchronization in Complex Oscillator Networks and Smart Grids

    Energy Technology Data Exchange (ETDEWEB)

    Dorfler, Florian [Los Alamos National Laboratory; Chertkov, Michael [Los Alamos National Laboratory; Bullo, Francesco [Center for Control, Dynamical Systems and Computation, University of California at Santa Babara, Santa Barbara CA

    2012-07-24

    The emergence of synchronization in a network of coupled oscillators is a fascinating topic in various scientific disciplines. A coupled oscillator network is characterized by a population of heterogeneous oscillators and a graph describing the interaction among them. It is known that a strongly coupled and sufficiently homogeneous network synchronizes, but the exact threshold from incoherence to synchrony is unknown. Here we present a novel, concise, and closed-form condition for synchronization of the fully nonlinear, non-equilibrium, and dynamic network. Our synchronization condition can be stated elegantly in terms of the network topology and parameters, or equivalently in terms of an intuitive, linear, and static auxiliary system. Our results significantly improve upon the existing conditions advocated thus far, they are provably exact for various interesting network topologies and parameters, they are statistically correct for almost all networks, and they can be applied equally to synchronization phenomena arising in physics and biology as well as in engineered oscillator networks such as electric power networks. We illustrate the validity, the accuracy, and the practical applicability of our results in complex networks scenarios and in smart grid applications.

  9. Clock Synchronization in Wireless Sensor Networks: A New Model and Analysis Approach Based on Networked Control Perspective

    Directory of Open Access Journals (Sweden)

    Wang Ting

    2014-01-01

    Full Text Available Motivated by the importance of the clock synchronization in wireless sensor networks (WSNs, this paper proposes a new research approach and model approach, which quantitatively analyzes clock synchronization from the perspective of modern control theory. Two kinds of control strategies are used as examples to analyze the effect of the control strategy on clock synchronization from different perspectives, namely, the single-step optimal control and the LQG global optimal control. The proposed method establishes a state space model for clock relationship, thus making dimension extension and parameter identification easier, and is robust to changes under the condition of node failures and new nodes. And through the design of different control strategies and performance index functions, the method can satisfy various requirements of the synchronization precision, convergence speed, energy consumption and the computational complexity, and so on. Finally, the simulations show that the synchronization accuracy of the proposed method is higher than that of the existing protocol, and the former convergence speed of the synchronization error is faster.

  10. Synchronization of a class of chaotic signals via robust observer design

    Energy Technology Data Exchange (ETDEWEB)

    Aguilar-Lopez, Ricardo [Departamento de Energia, Universidad Autonoma Metropolitana - Azcapotzalco, San Pablo 180, Reynosa-Tamaulipas, Azcapotzalco 02200, Mexico, D.F. (Mexico)], E-mail: raguilar@correo.azc.uam.mx; Martinez-Guerra, Rafael [Departamento de Energia, Universidad Autonoma Metropolitana - Azcapotzalco, San Pablo 180, Reynosa-Tamaulipas, Azcapotzalco 02200, Mexico, D.F. (Mexico); Departamento de Control Automatico, CINVESTAV IPN, Apartado Postal 14-740, Mexico, D.F. C.P. 07360 (Mexico)], E-mail: rguerra@ctrl.cinvestav.mx

    2008-07-15

    In this paper the signal synchronization of a class of chaotic systems based on robust observer design is tackled. The task is the synchronization of the signals generated by two Chen oscillators with different initial condition. The proposed observer is robust against model uncertainties and noisy output measurements. An alternative system representation is proposed to transform the measured disturbance onto system disturbance, which leads a more adequate observer structure. The proposed methodology contains an uncertainty estimator based on the predictive contribution to infer the unobservable uncertainties and corrective contribution to estimate the observable uncertainties; which provides robustness against noisy measurements and model uncertainties. Convergence analysis of the proposed estimation methodology is realized, analyzing the dynamic equation of the estimation error, where asymptotic convergence is shown. Numerical experiments illustrate the good performance of the proposed methodology.

  11. Synchronization of a class of chaotic signals via robust observer design

    International Nuclear Information System (INIS)

    Aguilar-Lopez, Ricardo; Martinez-Guerra, Rafael

    2008-01-01

    In this paper the signal synchronization of a class of chaotic systems based on robust observer design is tackled. The task is the synchronization of the signals generated by two Chen oscillators with different initial condition. The proposed observer is robust against model uncertainties and noisy output measurements. An alternative system representation is proposed to transform the measured disturbance onto system disturbance, which leads a more adequate observer structure. The proposed methodology contains an uncertainty estimator based on the predictive contribution to infer the unobservable uncertainties and corrective contribution to estimate the observable uncertainties; which provides robustness against noisy measurements and model uncertainties. Convergence analysis of the proposed estimation methodology is realized, analyzing the dynamic equation of the estimation error, where asymptotic convergence is shown. Numerical experiments illustrate the good performance of the proposed methodology

  12. Synchronization in Complex Networks of Nonlinear Dynamical Systems

    CERN Document Server

    Wu, Chai Wah

    2007-01-01

    This book brings together two emerging research areas: synchronization in coupled nonlinear systems and complex networks, and study conditions under which a complex network of dynamical systems synchronizes. While there are many texts that study synchronization in chaotic systems or properties of complex networks, there are few texts that consider the intersection of these two very active and interdisciplinary research areas. The main theme of this book is that synchronization conditions can be related to graph theoretical properties of the underlying coupling topology. The book introduces ide

  13. Perfect synchronization in networks of phase-frustrated oscillators

    Science.gov (United States)

    Kundu, Prosenjit; Hens, Chittaranjan; Barzel, Baruch; Pal, Pinaki

    2017-11-01

    Synchronizing phase-frustrated Kuramoto oscillators, a challenge that has found applications from neuronal networks to the power grid, is an eluding problem, as even small phase lags cause the oscillators to avoid synchronization. Here we show, constructively, how to strategically select the optimal frequency set, capturing the natural frequencies of all oscillators, for a given network and phase lags, that will ensure perfect synchronization. We find that high levels of synchronization are sustained in the vicinity of the optimal set, allowing for some level of deviation in the frequencies without significant degradation of synchronization. Demonstrating our results on first- and second-order phase-frustrated Kuramoto dynamics, we implement them on both model and real power grid networks, showing how to achieve synchronization in a phase-frustrated environment.

  14. Synchronization in an array of coupled Boolean networks

    International Nuclear Information System (INIS)

    Li, Rui; Chu, Tianguang

    2012-01-01

    This Letter presents an analytical study of synchronization in an array of coupled deterministic Boolean networks. A necessary and sufficient criterion for synchronization is established based on algebraic representations of logical dynamics in terms of the semi-tensor product of matrices. Some basic properties of a synchronized array of Boolean networks are then derived for the existence of transient states and the upper bound of the number of fixed points. Particularly, an interesting consequence indicates that a “large” mismatch between two coupled Boolean networks in the array may result in loss of synchrony in the entire system. Examples, including the Boolean model of coupled oscillations in the cell cycle, are given to illustrate the present results. -- Highlights: ► We analytically study synchronization in an array of coupled Boolean networks. ► The study is based on the algebraic representations of logical dynamics. ► A necessary and sufficient algebraic criterion for synchronization is established. ► It reveals some basic properties of a synchronized array of Boolean networks. ► A large mismatch between two coupled networks may result in the loss of synchrony.

  15. Partial synchronization in diffusively time-delay coupled oscillator networks

    NARCIS (Netherlands)

    Steur, E.; Oguchi, T.; Leeuwen, van C.; Nijmeijer, H.

    2012-01-01

    We study networks of diffusively time-delay coupled oscillatory units and we show that networks with certain symmetries can exhibit a form of incomplete synchronization called partial synchronization. We present conditions for the existence and stability of partial synchronization modes in networks

  16. Synchronization of mobile chaotic oscillator networks

    Energy Technology Data Exchange (ETDEWEB)

    Fujiwara, Naoya, E-mail: fujiwara@csis.u-tokyo.ac.jp [Center for Spatial Information Science, The University of Tokyo, 277-8568 Chiba (Japan); Kurths, Jürgen [Potsdam Institute for Climate Impact Research (PIK), 14473 Potsdam, Germany and Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen (United Kingdom); Díaz-Guilera, Albert [Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès 1, 08028 Barcelona, Spain and Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, Barcelona (Spain)

    2016-09-15

    We study synchronization of systems in which agents holding chaotic oscillators move in a two-dimensional plane and interact with nearby ones forming a time dependent network. Due to the uncertainty in observing other agents' states, we assume that the interaction contains a certain amount of noise that turns out to be relevant for chaotic dynamics. We find that a synchronization transition takes place by changing a control parameter. But this transition depends on the relative dynamic scale of motion and interaction. When the topology change is slow, we observe an intermittent switching between laminar and burst states close to the transition due to small noise. This novel type of synchronization transition and intermittency can happen even when complete synchronization is linearly stable in the absence of noise. We show that the linear stability of the synchronized state is not a sufficient condition for its stability due to strong fluctuations of the transverse Lyapunov exponent associated with a slow network topology change. Since this effect can be observed within the linearized dynamics, we can expect such an effect in the temporal networks with noisy chaotic oscillators, irrespective of the details of the oscillator dynamics. When the topology change is fast, a linearized approximation describes well the dynamics towards synchrony. These results imply that the fluctuations of the finite-time transverse Lyapunov exponent should also be taken into account to estimate synchronization of the mobile contact networks.

  17. Synchronization of mobile chaotic oscillator networks

    International Nuclear Information System (INIS)

    Fujiwara, Naoya; Kurths, Jürgen; Díaz-Guilera, Albert

    2016-01-01

    We study synchronization of systems in which agents holding chaotic oscillators move in a two-dimensional plane and interact with nearby ones forming a time dependent network. Due to the uncertainty in observing other agents' states, we assume that the interaction contains a certain amount of noise that turns out to be relevant for chaotic dynamics. We find that a synchronization transition takes place by changing a control parameter. But this transition depends on the relative dynamic scale of motion and interaction. When the topology change is slow, we observe an intermittent switching between laminar and burst states close to the transition due to small noise. This novel type of synchronization transition and intermittency can happen even when complete synchronization is linearly stable in the absence of noise. We show that the linear stability of the synchronized state is not a sufficient condition for its stability due to strong fluctuations of the transverse Lyapunov exponent associated with a slow network topology change. Since this effect can be observed within the linearized dynamics, we can expect such an effect in the temporal networks with noisy chaotic oscillators, irrespective of the details of the oscillator dynamics. When the topology change is fast, a linearized approximation describes well the dynamics towards synchrony. These results imply that the fluctuations of the finite-time transverse Lyapunov exponent should also be taken into account to estimate synchronization of the mobile contact networks.

  18. Synchronization of mobile chaotic oscillator networks.

    Science.gov (United States)

    Fujiwara, Naoya; Kurths, Jürgen; Díaz-Guilera, Albert

    2016-09-01

    We study synchronization of systems in which agents holding chaotic oscillators move in a two-dimensional plane and interact with nearby ones forming a time dependent network. Due to the uncertainty in observing other agents' states, we assume that the interaction contains a certain amount of noise that turns out to be relevant for chaotic dynamics. We find that a synchronization transition takes place by changing a control parameter. But this transition depends on the relative dynamic scale of motion and interaction. When the topology change is slow, we observe an intermittent switching between laminar and burst states close to the transition due to small noise. This novel type of synchronization transition and intermittency can happen even when complete synchronization is linearly stable in the absence of noise. We show that the linear stability of the synchronized state is not a sufficient condition for its stability due to strong fluctuations of the transverse Lyapunov exponent associated with a slow network topology change. Since this effect can be observed within the linearized dynamics, we can expect such an effect in the temporal networks with noisy chaotic oscillators, irrespective of the details of the oscillator dynamics. When the topology change is fast, a linearized approximation describes well the dynamics towards synchrony. These results imply that the fluctuations of the finite-time transverse Lyapunov exponent should also be taken into account to estimate synchronization of the mobile contact networks.

  19. Synchronization in slowly switching networks of coupled oscillators

    Science.gov (United States)

    Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Boccaletti, S.

    2016-01-01

    Networks whose structure of connections evolves in time constitute a big challenge in the study of synchronization, in particular when the time scales for the evolution of the graph topology are comparable with (or even longer than) those pertinent to the units’ dynamics. We here focus on networks with a slow-switching structure, and show that the necessary conditions for synchronization, i.e. the conditions for which synchronization is locally stable, are determined by the time average of the largest Lyapunov exponents of transverse modes of the switching topologies. Comparison between fast- and slow-switching networks allows elucidating that slow-switching processes prompt synchronization in the cases where the Master Stability Function is concave, whereas fast-switching schemes facilitate synchronization for convex curves. Moreover, the condition of slow-switching enables the introduction of a control strategy for inducing synchronization in networks with arbitrary structure and coupling strength, which is of evident relevance for broad applications in real world systems. PMID:27779253

  20. Detection of generalized synchronization using echo state networks

    Science.gov (United States)

    Ibáñez-Soria, D.; Garcia-Ojalvo, J.; Soria-Frisch, A.; Ruffini, G.

    2018-03-01

    Generalized synchronization between coupled dynamical systems is a phenomenon of relevance in applications that range from secure communications to physiological modelling. Here, we test the capabilities of reservoir computing and, in particular, echo state networks for the detection of generalized synchronization. A nonlinear dynamical system consisting of two coupled Rössler chaotic attractors is used to generate temporal series consisting of time-locked generalized synchronized sequences interleaved with unsynchronized ones. Correctly tuned, echo state networks are able to efficiently discriminate between unsynchronized and synchronized sequences even in the presence of relatively high levels of noise. Compared to other state-of-the-art techniques of synchronization detection, the online capabilities of the proposed Echo State Network based methodology make it a promising choice for real-time applications aiming to monitor dynamical synchronization changes in continuous signals.

  1. Robust function projective synchronization of a class of uncertain chaotic systems

    International Nuclear Information System (INIS)

    Shen Liqun; Liu Wanyu; Ma Jianwei

    2009-01-01

    In this paper, the function projective synchronization problem of chaotic systems is investigated, where parameter mismatch exists between the drive system and the response system. Based on Lyapunov stability theory, a novel robust function projective synchronization scheme is proposed. And the parameter mismatch problem is also solved. Simulation results of Lorenz system and Chen system verify the effectiveness of the proposed control scheme.

  2. Small-world networks exhibit pronounced intermittent synchronization

    Science.gov (United States)

    Choudhary, Anshul; Mitra, Chiranjit; Kohar, Vivek; Sinha, Sudeshna; Kurths, Jürgen

    2017-11-01

    We report the phenomenon of temporally intermittently synchronized and desynchronized dynamics in Watts-Strogatz networks of chaotic Rössler oscillators. We consider topologies for which the master stability function (MSF) predicts stable synchronized behaviour, as the rewiring probability (p) is tuned from 0 to 1. MSF essentially utilizes the largest non-zero Lyapunov exponent transversal to the synchronization manifold in making stability considerations, thereby ignoring the other Lyapunov exponents. However, for an N-node networked dynamical system, we observe that the difference in its Lyapunov spectra (corresponding to the N - 1 directions transversal to the synchronization manifold) is crucial and serves as an indicator of the presence of intermittently synchronized behaviour. In addition to the linear stability-based (MSF) analysis, we further provide global stability estimate in terms of the fraction of state-space volume shared by the intermittently synchronized state, as p is varied from 0 to 1. This fraction becomes appreciably large in the small-world regime, which is surprising, since this limit has been otherwise considered optimal for synchronized dynamics. Finally, we characterize the nature of the observed intermittency and its dominance in state-space as network rewiring probability (p) is varied.

  3. Remote synchronization reveals network symmetries and functional modules.

    Science.gov (United States)

    Nicosia, Vincenzo; Valencia, Miguel; Chavez, Mario; Díaz-Guilera, Albert; Latora, Vito

    2013-04-26

    We study a Kuramoto model in which the oscillators are associated with the nodes of a complex network and the interactions include a phase frustration, thus preventing full synchronization. The system organizes into a regime of remote synchronization where pairs of nodes with the same network symmetry are fully synchronized, despite their distance on the graph. We provide analytical arguments to explain this result, and we show how the frustration parameter affects the distribution of phases. An application to brain networks suggests that anatomical symmetry plays a role in neural synchronization by determining correlated functional modules across distant locations.

  4. Simple robust technique using time delay estimation for the control and synchronization of Lorenz systems

    International Nuclear Information System (INIS)

    Jin, Maolin; Chang, Pyung Hun

    2009-01-01

    This work presents two simple and robust techniques based on time delay estimation for the respective control and synchronization of chaos systems. First, one of these techniques is applied to the control of a chaotic Lorenz system with both matched and mismatched uncertainties. The nonlinearities in the Lorenz system is cancelled by time delay estimation and desired error dynamics is inserted. Second, the other technique is applied to the synchronization of the Lue system and the Lorenz system with uncertainties. The synchronization input consists of three elements that have transparent and clear meanings. Since time delay estimation enables a very effective and efficient cancellation of disturbances and nonlinearities, the techniques turn out to be simple and robust. Numerical simulation results show fast, accurate and robust performance of the proposed techniques, thereby demonstrating their effectiveness for the control and synchronization of Lorenz systems.

  5. An Inter-Networking Mechanism with Stepwise Synchronization for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Masayuki Murata

    2011-08-01

    Full Text Available To realize the ambient information society, multiple wireless networks deployed in the region and devices carried by users are required to cooperate with each other. Since duty cycles and operational frequencies are different among networks, we need a mechanism to allow networks to efficiently exchange messages. For this purpose, we propose a novel inter-networking mechanism where two networks are synchronized with each other in a moderate manner, which we call stepwise synchronization. With our proposal, to bridge the gap between intrinsic operational frequencies, nodes near the border of networks adjust their operational frequencies in a stepwise fashion based on the pulse-coupled oscillator model as a fundamental theory of synchronization. Through simulation experiments, we show that the communication delay and the energy consumption of border nodes are reduced, which enables wireless sensor networks to communicate longer with each other.

  6. Mobility-aware Hybrid Synchronization for Wireless Sensor Network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Prasad, Neeli R.; Prasad, Ramjee

    2015-01-01

    Random mobility of node causes the frequent changes in the network dynamics causing the increased cost in terms of energy and bandwidth. It needs the additional efforts to synchronize the activities of nodes during data collection and transmission in Wireless Sensor Networks (WSNs). A key challenge...... in maintaining the effective data collection and transmission is to schedule and synchronize the activities of the nodes with the global clock. This paper proposes the Mobility-aware Hybrid Synchronization Algorithm (MHS) which works on the formation of cluster based on spanning tree mechanism (SPT). Nodes used...... for formation of the network have random mobility and heterogeneous in terms of energy with static sink. The nodes in the cluster and cluster heads in the network are synchronized with the notion of global time scale. In the initial stage, the algorithm establishes the hierarchical structure of the network...

  7. Complex networks: when random walk dynamics equals synchronization

    International Nuclear Information System (INIS)

    Kriener, Birgit; Anand, Lishma; Timme, Marc

    2012-01-01

    Synchrony prevalently emerges from the interactions of coupled dynamical units. For simple systems such as networks of phase oscillators, the asymptotic synchronization process is assumed to be equivalent to a Markov process that models standard diffusion or random walks on the same network topology. In this paper, we analytically derive the conditions for such equivalence for networks of pulse-coupled oscillators, which serve as models for neurons and pacemaker cells interacting by exchanging electric pulses or fireflies interacting via light flashes. We find that the pulse synchronization process is less simple, but there are classes of, e.g., network topologies that ensure equivalence. In particular, local dynamical operators are required to be doubly stochastic. These results provide a natural link between stochastic processes and deterministic synchronization on networks. Tools for analyzing diffusion (or, more generally, Markov processes) may now be transferred to pin down features of synchronization in networks of pulse-coupled units such as neural circuits. (paper)

  8. Impulsive Cluster Synchronization in Community Network with Nonidentical Nodes

    International Nuclear Information System (INIS)

    Deng Liping; Wu Zhaoyan

    2012-01-01

    In this paper, cluster synchronization in community network with nonidentical nodes and impulsive effects is investigated. Community networks with two kinds of topological structure are investigated. Positive weighted network is considered first and external pinning controllers are designed for achieving cluster synchronization. Cooperative and competitive network under some assumptions is investigated as well and can achieve cluster synchronization with only impulsive controllers. Based on the stability analysis of impulsive differential equation and the Lyapunov stability theory, several simple and useful synchronization criteria are derived. Finally, numerical simulations are provided to verify the effectiveness of the derived results.

  9. Bifurcation behaviors of synchronized regions in logistic map networks with coupling delay

    International Nuclear Information System (INIS)

    Tang, Longkun; Wu, Xiaoqun; Lu, Jun-an; Lü, Jinhu

    2015-01-01

    Network synchronized regions play an extremely important role in network synchronization according to the master stability function framework. This paper focuses on network synchronous state stability via studying the effects of nodal dynamics, coupling delay, and coupling way on synchronized regions in Logistic map networks. Theoretical and numerical investigations show that (1) network synchronization is closely associated with its nodal dynamics. Particularly, the synchronized region bifurcation points through which the synchronized region switches from one type to another are in good agreement with those of the uncoupled node system, and chaotic nodal dynamics can greatly impede network synchronization. (2) The coupling delay generally impairs the synchronizability of Logistic map networks, which is also dominated by the parity of delay for some nodal parameters. (3) A simple nonlinear coupling facilitates network synchronization more than the linear one does. The results found in this paper will help to intensify our understanding for the synchronous state stability in discrete-time networks with coupling delay

  10. Robust synchronization of unified chaotic systems via sliding mode control

    International Nuclear Information System (INIS)

    Yan Junjuh; Yang Yisung; Chiang Tsungying; Chen Chingyuan

    2007-01-01

    This paper investigates the chaos synchronization problem for a class of uncertain master-slave unified chaotic systems. Based on the sliding mode control technique, a robust control scheme is established which guarantees the occurrence of a sliding motion of error states even when the parameter uncertainty and external perturbation are present. Furthermore, a novel proportional-integral (PI) switching surface is introduced for determining the synchronization performance of systems in the sliding mode motion. Simulation results are proposed to demonstrate the effectiveness of the method

  11. Global synchronization of a class of delayed complex networks

    International Nuclear Information System (INIS)

    Li Ping; Yi Zhang; Zhang Lei

    2006-01-01

    Global synchronization of a class of complex networks with time-varying delays is investigated in this paper. Some sufficient conditions are derived. These conditions show that the synchronization of delayed complex networks can be determined by their topologies. In addition, these conditions are simply represented in terms of the networks coupling matrix and are easy to be checked. A typical example of complex networks with chaotic nodes is employed to illustrate the obtained global synchronization results

  12. Synchronization of the small-world neuronal network with unreliable synapses

    International Nuclear Information System (INIS)

    Li, Chunguang; Zheng, Qunxian

    2010-01-01

    As is well known, synchronization phenomena are ubiquitous in neuronal systems. Recently a lot of work concerning the synchronization of the neuronal network has been accomplished. In these works, the synapses are usually considered reliable, but experimental results show that, in biological neuronal networks, synapses are usually unreliable. In our previous work, we have studied the synchronization of the neuronal network with unreliable synapses; however, we have not paid attention to the effect of topology on the synchronization of the neuronal network. Several recent studies have found that biological neuronal networks have typical properties of small-world networks, characterized by a short path length and high clustering coefficient. In this work, mainly based on the small-world neuronal network (SWNN) with inhibitory neurons, we study the effect of network topology on the synchronization of the neuronal network with unreliable synapses. Together with the network topology, the effects of the GABAergic reversal potential, time delay and noise are also considered. Interestingly, we found a counter-intuitive phenomenon for the SWNN with specific shortcut adding probability, that is, the less reliable the synapses, the better the synchronization performance of the SWNN. We also consider the effects of both local noise and global noise in this work. It is shown that these two different types of noise have distinct effects on the synchronization: one is negative and the other is positive

  13. Synchronization transmission of laser pattern signal within uncertain switched network

    Science.gov (United States)

    Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

    2017-06-01

    We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

  14. Pinning synchronization of a mobile agent network

    International Nuclear Information System (INIS)

    Wang, Lei; Sun, You-xian

    2009-01-01

    We investigate the problem of controlling a group of mobile agents in a plane in order to move them towards a desired orbit via pinning control, in which each agent is associated with a chaotic oscillator coupled with those of neighboring agents, and the pinning strategy is to have the common linear feedback acting on a small fraction of agents by random selection. We explore the effects of the pinning probability, feedback gains and agent density in the pinning synchronization of a mobile agent network under a fast-switching constraint, and perform numerical simulations for validation. In particular, we show that there exists a critical pinning density for network synchronization with an unbounded region: above the threshold, the dynamical network can be controlled by pinning; below it, anarchy prevails. And for the network with a single bounded synchronization region, pinning control has little effect as regards enhancing network synchronizability

  15. Synchronization in node of complex networks consist of complex chaotic system

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Qiang, E-mail: qiangweibeihua@163.com [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024 (China); Xie, Cheng-jun [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Liu, Hong-jun [School of Information Engineering, Weifang Vocational College, Weifang, 261041 (China); Li, Yan-hui [The Library, Weifang Vocational College, Weifang, 261041 (China)

    2014-07-15

    A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

  16. The relationship between synchronization and percolation for regular networks

    Science.gov (United States)

    Li, Zhe; Ren, Tao; Xu, Yanjie; Jin, Jianyu

    2018-02-01

    Synchronization and percolation are two essential phenomena in complex dynamical networks. They have been studied widely, but previously treated as unrelated. In this paper, the relationship between synchronization and percolation are revealed for regular networks. Firstly, we discovered a bridge between synchronization and percolation by using the eigenvalues of the Laplacian matrix to describe the synchronizability and using the eigenvalues of the adjacency matrix to describe the percolation threshold. Then, we proposed a method to find the relationship for regular networks based on the topology of networks. Particularly, if the degree distribution of the network is subject to delta function, we show that only the eigenvalues of the adjacency matrix need to be calculated. Finally, several examples are provided to demonstrate how to apply our proposed method to discover the relationship between synchronization and percolation for regular networks.

  17. Synchronization coupled systems to complex networks

    CERN Document Server

    Boccaletti, Stefano; del Genio, Charo I; Amann, Andreas

    2018-01-01

    A modern introduction to synchronization phenomena, this text presents recent discoveries and the current state of research in the field, from low-dimensional systems to complex networks. The book describes some of the main mechanisms of collective behaviour in dynamical systems, including simple coupled systems, chaotic systems, and systems of infinite-dimension. After introducing the reader to the basic concepts of nonlinear dynamics, the book explores the main synchronized states of coupled systems and describes the influence of noise and the occurrence of synchronous motion in multistable and spatially-extended systems. Finally, the authors discuss the underlying principles of collective dynamics on complex networks, providing an understanding of how networked systems are able to function as a whole in order to process information, perform coordinated tasks, and respond collectively to external perturbations. The demonstrations, numerous illustrations and application examples will help advanced graduate s...

  18. Relaxation of synchronization on complex networks.

    Science.gov (United States)

    Son, Seung-Woo; Jeong, Hawoong; Hong, Hyunsuk

    2008-07-01

    We study collective synchronization in a large number of coupled oscillators on various complex networks. In particular, we focus on the relaxation dynamics of the synchronization, which is important from the viewpoint of information transfer or the dynamics of system recovery from a perturbation. We measure the relaxation time tau that is required to establish global synchronization by varying the structural properties of the networks. It is found that the relaxation time in a strong-coupling regime (K>Kc) logarithmically increases with network size N , which is attributed to the initial random phase fluctuation given by O(N-1/2) . After elimination of the initial-phase fluctuation, the relaxation time is found to be independent of the system size; this implies that the local interaction that depends on the structural connectivity is irrelevant in the relaxation dynamics of the synchronization in the strong-coupling regime. The relaxation dynamics is analytically derived in a form independent of the system size, and it exhibits good consistency with numerical simulations. As an application, we also explore the recovery dynamics of the oscillators when perturbations enter the system.

  19. A network of networks model to study phase synchronization using structural connection matrix of human brain

    Science.gov (United States)

    Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

    2018-04-01

    The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

  20. Synchronization of complex delayed dynamical networks with nonlinearly coupled nodes

    International Nuclear Information System (INIS)

    Liu Tao; Zhao Jun; Hill, David J.

    2009-01-01

    In this paper, we study the global synchronization of nonlinearly coupled complex delayed dynamical networks with both directed and undirected graphs. Via Lyapunov-Krasovskii stability theory and the network topology, we investigate the global synchronization of such networks. Under the assumption that coupling coefficients are known, a family of delay-independent decentralized nonlinear feedback controllers are designed to globally synchronize the networks. When coupling coefficients are unavailable, an adaptive mechanism is introduced to synthesize a family of delay-independent decentralized adaptive controllers which guarantee the global synchronization of the uncertain networks. Two numerical examples of directed and undirected delayed dynamical network are given, respectively, using the Lorenz system as the nodes of the networks, which demonstrate the effectiveness of proposed results.

  1. Global synchronization of general delayed complex networks with stochastic disturbances

    International Nuclear Information System (INIS)

    Tu Li-Lan

    2011-01-01

    In this paper, global synchronization of general delayed complex networks with stochastic disturbances, which is a zero-mean real scalar Wiener process, is investigated. The networks under consideration are continuous-time networks with time-varying delay. Based on the stochastic Lyapunov stability theory, Ito's differential rule and the linear matrix inequality (LMI) optimization technique, several delay-dependent synchronous criteria are established, which guarantee the asymptotical mean-square synchronization of drive networks and response networks with stochastic disturbances. The criteria are expressed in terms of LMI, which can be easily solved using the Matlab LMI Control Toolbox. Finally, two examples show the effectiveness and feasibility of the proposed synchronous conditions. (general)

  2. Stochastic synchronization in finite size spiking networks

    Science.gov (United States)

    Doiron, Brent; Rinzel, John; Reyes, Alex

    2006-09-01

    We study a stochastic synchronization of spiking activity in feedforward networks of integrate-and-fire model neurons. A stochastic mean field analysis shows that synchronization occurs only when the network size is sufficiently small. This gives evidence that the dynamics, and hence processing, of finite size populations can be drastically different from that observed in the infinite size limit. Our results agree with experimentally observed synchrony in cortical networks, and further strengthen the link between synchrony and propagation in cortical systems.

  3. Complete and phase synchronization in a heterogeneous small-world neuronal network

    International Nuclear Information System (INIS)

    Fang, Han; Qi-Shao, Lu; Quan-Bao, Ji; Marian, Wiercigroch

    2009-01-01

    Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh–Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony. (general)

  4. Extension of Pairwise Broadcast Clock Synchronization for Multicluster Sensor Networks

    Directory of Open Access Journals (Sweden)

    Bruce W. Suter

    2008-01-01

    Full Text Available Time synchronization is crucial for wireless sensor networks (WSNs in performing a number of fundamental operations such as data coordination, power management, security, and localization. The Pairwise Broadcast Synchronization (PBS protocol was recently proposed to minimize the number of timing messages required for global network synchronization, which enables the design of highly energy-efficient WSNs. However, PBS requires all nodes in the network to lie within the communication ranges of two leader nodes, a condition which might not be available in some applications. This paper proposes an extension of PBS to the more general class of sensor networks. Based on the hierarchical structure of the network, an energy-efficient pair selection algorithm is proposed to select the best pairwise synchronization sequence to reduce the overall energy consumption. It is shown that in a multicluster networking environment, PBS requires a far less number of timing messages than other well-known synchronization protocols and incurs no loss in synchronization accuracy. Moreover, the proposed scheme presents significant energy savings for densely deployed WSNs.

  5. Complete synchronization on multi-layer center dynamical networks

    International Nuclear Information System (INIS)

    Liu Meng; Shao Yingying; Fu Xinchu

    2009-01-01

    In this paper, complete synchronization of three-layer center networks is studied. By using linear stability analysis approach, several different coupling schemes of three-layer center networks with the Logistic map local dynamics are discussed, and the stability conditions for synchronization are illustrated via some examples.

  6. Practical synchronization on complex dynamical networks via optimal pinning control

    Science.gov (United States)

    Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

    2015-07-01

    We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

  7. Modular networks with delayed coupling: Synchronization and frequency control

    Science.gov (United States)

    Maslennikov, Oleg V.; Nekorkin, Vladimir I.

    2014-07-01

    We study the collective dynamics of modular networks consisting of map-based neurons which generate irregular spike sequences. Three types of intramodule topology are considered: a random Erdös-Rényi network, a small-world Watts-Strogatz network, and a scale-free Barabási-Albert network. The interaction between the neurons of different modules is organized by relatively sparse connections with time delay. For all the types of the network topology considered, we found that with increasing delay two regimes of module synchronization alternate with each other: inphase and antiphase. At the same time, the average rate of collective oscillations decreases within each of the time-delay intervals corresponding to a particular synchronization regime. A dual role of the time delay is thus established: controlling a synchronization mode and degree and controlling an average network frequency. Furthermore, we investigate the influence on the modular synchronization by other parameters: the strength of intermodule coupling and the individual firing rate.

  8. Generalized Mutual Synchronization between Two Controlled Interdependent Networks

    OpenAIRE

    Xu, Quan; Zhuang, Shengxian; Hu, Dan; Zeng, Yingfeng; Xiao, Jian

    2014-01-01

    This paper mainly focuses on the generalized mutual synchronization between two controlled interdependent networks. First, we propose the general model of controlled interdependent networks $A$ and $B$ with time-varying internetwork delays coupling. Then, by constructing Lyapunov functions and utilizing adaptive control technique, some sufficient conditions are established to ensure that the mutual synchronization errors between the state variables of networks $A$ and $B$ can asymptotically c...

  9. H-Infinity robust controller design for the synchronization of master-slave chaotic systems with disturbance input

    Directory of Open Access Journals (Sweden)

    Hamid Reza Karimi

    2012-01-01

    Full Text Available This paper is concerned with the robust control problems for the synchronization of master-slave chaotic systems with disturbance input. By constructing a series of Lyapunov functions, novel H-Infinity robust synchronization controllers are designed, whose control regulation possess the characteristic of simpleness and explicitness. Finally, numerical simulations are provided to demonstrate the effectiveness of the proposed techniques.

  10. Generalized projective synchronization of two coupled complex networks of different sizes

    International Nuclear Information System (INIS)

    Li Ke-Zan; He En; Zeng Zhao-Rong; Chi, K. Tse

    2013-01-01

    We investigate a new generalized projective synchronization between two complex dynamical networks of different sizes. To the best of our knowledge, most of the current studies on projective synchronization have dealt with coupled networks of the same size. By generalized projective synchronization, we mean that the states of the nodes in each network can realize complete synchronization, and the states of a pair of nodes from both networks can achieve projective synchronization. Using the stability theory of the dynamical system, several sufficient conditions for guaranteeing the existence of the generalized projective synchronization under feedback control and adaptive control are obtained. As an example, we use Chua's circuits to demonstrate the effectiveness of our proposed approach

  11. Robustness of airline route networks

    Science.gov (United States)

    Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

    2016-03-01

    Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

  12. Limitations and tradeoffs in synchronization of large-scale networks with uncertain links

    Science.gov (United States)

    Diwadkar, Amit; Vaidya, Umesh

    2016-01-01

    The synchronization of nonlinear systems connected over large-scale networks has gained popularity in a variety of applications, such as power grids, sensor networks, and biology. Stochastic uncertainty in the interconnections is a ubiquitous phenomenon observed in these physical and biological networks. We provide a size-independent network sufficient condition for the synchronization of scalar nonlinear systems with stochastic linear interactions over large-scale networks. This sufficient condition, expressed in terms of nonlinear dynamics, the Laplacian eigenvalues of the nominal interconnections, and the variance and location of the stochastic uncertainty, allows us to define a synchronization margin. We provide an analytical characterization of important trade-offs between the internal nonlinear dynamics, network topology, and uncertainty in synchronization. For nearest neighbour networks, the existence of an optimal number of neighbours with a maximum synchronization margin is demonstrated. An analytical formula for the optimal gain that produces the maximum synchronization margin allows us to compare the synchronization properties of various complex network topologies. PMID:27067994

  13. Robustness and structure of complex networks

    Science.gov (United States)

    Shao, Shuai

    This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks

  14. Synchronization in networks with multiple interaction layers

    Science.gov (United States)

    del Genio, Charo I.; Gómez-Gardeñes, Jesús; Bonamassa, Ivan; Boccaletti, Stefano

    2016-01-01

    The structure of many real-world systems is best captured by networks consisting of several interaction layers. Understanding how a multilayered structure of connections affects the synchronization properties of dynamical systems evolving on top of it is a highly relevant endeavor in mathematics and physics and has potential applications in several socially relevant topics, such as power grid engineering and neural dynamics. We propose a general framework to assess the stability of the synchronized state in networks with multiple interaction layers, deriving a necessary condition that generalizes the master stability function approach. We validate our method by applying it to a network of Rössler oscillators with a double layer of interactions and show that highly rich phenomenology emerges from this. This includes cases where the stability of synchronization can be induced even if both layers would have individually induced unstable synchrony, an effect genuinely arising from the true multilayer structure of the interactions among the units in the network. PMID:28138540

  15. Exponential Synchronization of Uncertain Complex Dynamical Networks with Delay Coupling

    International Nuclear Information System (INIS)

    Wang Lifu; Kong Zhi; Jing Yuanwei

    2010-01-01

    This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches. (general)

  16. Approximation methods for the stability analysis of complete synchronization on duplex networks

    Science.gov (United States)

    Han, Wenchen; Yang, Junzhong

    2018-01-01

    Recently, the synchronization on multi-layer networks has drawn a lot of attention. In this work, we study the stability of the complete synchronization on duplex networks. We investigate effects of coupling function on the complete synchronization on duplex networks. We propose two approximation methods to deal with the stability of the complete synchronization on duplex networks. In the first method, we introduce a modified master stability function and, in the second method, we only take into consideration the contributions of a few most unstable transverse modes to the stability of the complete synchronization. We find that both methods work well for predicting the stability of the complete synchronization for small networks. For large networks, the second method still works pretty well.

  17. Phase synchronization of non-Abelian oscillators on small-world networks

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Zhi-Ming [College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Zhao, Ming [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China); Zhou, Tao [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China)]. E-mail: zhutou@ustc.edu; Zhu, Chen-Ping [College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Wang, Bing-Hong [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China)

    2007-02-26

    In this Letter, by extending the concept of Kuramoto oscillator to the left-invariant flow on general Lie group, we investigate the generalized phase synchronization on networks. The analyses and simulations of some typical dynamical systems on Watts-Strogatz networks are given, including the n-dimensional torus, the identity component of 3-dimensional general linear group, the special unitary group, and the special orthogonal group. In all cases, the greater disorder of networks will predict better synchronizability, and the small-world effect ensures the global synchronization for sufficiently large coupling strength. The collective synchronized behaviors of many dynamical systems, such as the integrable systems, the two-state quantum systems and the top systems, can be described by the present phase synchronization frame. In addition, it is intuitive that the low-dimensional systems are more easily to synchronize, however, to our surprise, we found that the high-dimensional systems display obviously synchronized behaviors in regular networks, while these phenomena cannot be observed in low-dimensional systems.

  18. Phase synchronization of non-Abelian oscillators on small-world networks

    International Nuclear Information System (INIS)

    Gu, Zhi-Ming; Zhao, Ming; Zhou, Tao; Zhu, Chen-Ping; Wang, Bing-Hong

    2007-01-01

    In this Letter, by extending the concept of Kuramoto oscillator to the left-invariant flow on general Lie group, we investigate the generalized phase synchronization on networks. The analyses and simulations of some typical dynamical systems on Watts-Strogatz networks are given, including the n-dimensional torus, the identity component of 3-dimensional general linear group, the special unitary group, and the special orthogonal group. In all cases, the greater disorder of networks will predict better synchronizability, and the small-world effect ensures the global synchronization for sufficiently large coupling strength. The collective synchronized behaviors of many dynamical systems, such as the integrable systems, the two-state quantum systems and the top systems, can be described by the present phase synchronization frame. In addition, it is intuitive that the low-dimensional systems are more easily to synchronize, however, to our surprise, we found that the high-dimensional systems display obviously synchronized behaviors in regular networks, while these phenomena cannot be observed in low-dimensional systems

  19. Altered Synchronizations among Neural Networks in Geriatric Depression.

    Science.gov (United States)

    Wang, Lihong; Chou, Ying-Hui; Potter, Guy G; Steffens, David C

    2015-01-01

    Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

  20. The synchronization of FitzHugh–Nagumo neuron network coupled by gap junction

    International Nuclear Information System (INIS)

    Zhan Yong; Zhang Suhua; Zhao Tongjun; An Hailong; Zhang Zhendong; Han Yingrong; Liu Hui; Zhang Yuhong

    2008-01-01

    It is well known that the strong coupling can synchronize a network of nonlinear oscillators. Synchronization provides the basis of the remarkable computational performance of the brain. In this paper the FitzHugh–Nagumo neuron network is constructed. The dependence of the synchronization on the coupling strength, the noise intensity and the size of the neuron network has been discussed. The results indicate that the coupling among neurons works to improve the synchronization, and noise increases the neuron random dynamics and the local fluctuations; the larger the size of network, the worse the synchronization. The dependence of the synchronization on the strength of the electric synapse coupling and chemical synapse coupling has also been discussed, which proves that electric synapse coupling can enhance the synchronization of the neuron network largely

  1. Average contraction and synchronization of complex switched networks

    International Nuclear Information System (INIS)

    Wang Lei; Wang Qingguo

    2012-01-01

    This paper introduces an average contraction analysis for nonlinear switched systems and applies it to investigating the synchronization of complex networks of coupled systems with switching topology. For a general nonlinear system with a time-dependent switching law, a basic convergence result is presented according to average contraction analysis, and a special case where trajectories of a distributed switched system converge to a linear subspace is then investigated. Synchronization is viewed as the special case with all trajectories approaching the synchronization manifold, and is thus studied for complex networks of coupled oscillators with switching topology. It is shown that the synchronization of a complex switched network can be evaluated by the dynamics of an isolated node, the coupling strength and the time average of the smallest eigenvalue associated with the Laplacians of switching topology and the coupling fashion. Finally, numerical simulations illustrate the effectiveness of the proposed methods. (paper)

  2. Cluster synchronization in community network with hybrid coupling

    International Nuclear Information System (INIS)

    Yang, Lixin; Jiang, Jun; Liu, Xiaojun

    2016-01-01

    Highlights: • A community network model with hybrid coupling is proposed. • Control scheme is designed via combining adaptive external coupling strength and feedback control. • The influence of topology structure on synchronization of community network is discussed. - Abstract: A general model of community network with hybrid coupling is proposed in this paper. In the community network model with hybrid coupling, the inner connections are in the same type of coupling within the same community and in different types of coupling in different communities. The connections between different pair of communities are also nonidentical. Cluster synchronization of community network with hybrid coupling is investigated via adaptive couplings control scheme. Effective controllers are designed for constructing an effective control scheme and adjusting automatically the adaptive external coupling strength by taking external coupling strength as adaptive variables on a small fraction of network edges. Moreover, the impact of the topology on the synchronizability of community network is investigated. The numerical results reveal that the number of links between communities and the degree of the connector nodes have significant effects on the synchronization performance.

  3. Finite-Time Nonfragile Synchronization of Stochastic Complex Dynamical Networks with Semi-Markov Switching Outer Coupling

    Directory of Open Access Journals (Sweden)

    Rathinasamy Sakthivel

    2018-01-01

    Full Text Available The problem of robust nonfragile synchronization is investigated in this paper for a class of complex dynamical networks subject to semi-Markov jumping outer coupling, time-varying coupling delay, randomly occurring gain variation, and stochastic noise over a desired finite-time interval. In particular, the network topology is assumed to follow a semi-Markov process such that it may switch from one to another at different instants. In this paper, the random gain variation is represented by a stochastic variable that is assumed to satisfy the Bernoulli distribution with white sequences. Based on these hypotheses and the Lyapunov-Krasovskii stability theory, a new finite-time stochastic synchronization criterion is established for the considered network in terms of linear matrix inequalities. Moreover, the control design parameters that guarantee the required criterion are computed by solving a set of linear matrix inequality constraints. An illustrative example is finally given to show the effectiveness and advantages of the developed analytical results.

  4. Synchronization of Switched Interval Networks and Applications to Chaotic Neural Networks

    Directory of Open Access Journals (Sweden)

    Jinde Cao

    2013-01-01

    Full Text Available This paper investigates synchronization problem of switched delay networks with interval parameters uncertainty, based on the theories of the switched systems and drive-response technique, a mathematical model of the switched interval drive-response error system is established. Without constructing Lyapunov-Krasovskii functions, introducing matrix measure method for the first time to switched time-varying delay networks, combining Halanay inequality technique, synchronization criteria are derived for switched interval networks under the arbitrary switching rule, which are easy to verify in practice. Moreover, as an application, the proposed scheme is then applied to chaotic neural networks. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.

  5. Time Synchronized Wireless Sensor Network for Vibration Measurement

    Science.gov (United States)

    Uchimura, Yutaka; Nasu, Tadashi; Takahashi, Motoichi

    Network based wireless sensing has become an important area of research and various new applications for remote sensing are expected to emerge. One of the promising applications is structural health monitoring of building or civil engineering structure and it often requires vibration measurement. For the vibration measurement via wireless network, time synchronization is indispensable. In this paper, we introduce a newly developed time synchronized wireless sensor network system. The system employs IEEE 802.11 standard based TSF counter and sends the measured data with the counter value. TSF based synchronization enables consistency on common clock among different wireless nodes. We consider the scale effect on the synchronization accuracy and the effect is evaluated by stochastic analysis and simulation studies. A new wireless sensing system is developed and the hardware and software specifications are shown. The experiments are conducted in a reinforced concrete building and results show good performance enough for vibration measurement purpose.

  6. Phase synchronization on small-world networks with community structure

    International Nuclear Information System (INIS)

    Xiao-Hua, Wang; Li-Cheng, Jiao; Jian-She, Wu

    2010-01-01

    In this paper, we propose a simple model that can generate small-world network with community structure. The network is introduced as a tunable community organization with parameter r, which is directly measured by the ratio of inter- to intra-community connectivity, and a smaller r corresponds to a stronger community structure. The structure properties, including the degree distribution, clustering, the communication efficiency and modularity are also analysed for the network. In addition, by using the Kuramoto model, we investigated the phase synchronization on this network, and found that increasing the fuzziness of community structure will markedly enhance the network synchronizability; however, in an abnormal region (r ≤ 0.001), the network has even worse synchronizability than the case of isolated communities (r = 0). Furthermore, this network exhibits a remarkable synchronization behaviour in topological scales: the oscillators of high densely interconnected communities synchronize more easily, and more rapidly than the whole network. (general)

  7. A Robust Approach for Clock Offset Estimation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Kim Jang-Sub

    2010-01-01

    Full Text Available The maximum likelihood estimators (MLEs for the clock phase offset assuming a two-way message exchange mechanism between the nodes of a wireless sensor network were recently derived assuming Gaussian and exponential network delays. However, the MLE performs poorly in the presence of non-Gaussian or nonexponential network delay distributions. Currently, there is a need to develop clock synchronization algorithms that are robust to the distribution of network delays. This paper proposes a clock offset estimator based on the composite particle filter (CPF to cope with the possible asymmetries and non-Gaussianity of the network delay distributions. Also, a variant of the CPF approach based on the bootstrap sampling (BS is shown to exhibit good performance in the presence of reduced number of observations. Computer simulations illustrate that the basic CPF and its BS-based variant present superior performance than MLE under general random network delay distributions such as asymmetric Gaussian, exponential, Gamma, Weibull as well as various mixtures.

  8. Synchronization of Phase Oscillators in Networks with Certain Frequency Sequence

    International Nuclear Information System (INIS)

    Feng Yuan-Yuan; Wu Liang; Zhu Shi-Qun

    2014-01-01

    Synchronization of Kuramoto phase oscillators arranged in real complex neural networks is investigated. It is shown that the synchronization greatly depends on the sets of natural frequencies of the involved oscillators. The influence of network connectivity heterogeneity on synchronization depends particularly on the correlation between natural frequencies and node degrees. This finding implies a potential application that inhibiting the effects caused by the changes of network structure can be balanced out nicely by choosing the correlation parameter appropriately. (general)

  9. Synchronized Data Aggregation for Wireless Sensor Network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Prasad, Neeli R.; Prasad, Ramjee

    2014-01-01

    Wireless Sensor Networks (WSNs) are used for monitoring and data collection purposes. A key challenge in effective data collection is to schedule and synchronize the activities of the nodes with global clock. This paper proposes the Synchronized Data Aggregation Algorithm (SDA) using spanning tree...

  10. Pinning Synchronization of Linear Complex Coupling Synchronous Generators Network of Hydroelectric Generating Set

    Directory of Open Access Journals (Sweden)

    Xuefei Wu

    2014-01-01

    Full Text Available A novel linear complex system for hydroturbine-generator sets in multimachine power systems is suggested in this paper and synchronization of the power-grid networks is studied. The advanced graph theory and stability theory are combined to solve the problem. Here we derive a sufficient condition under which the synchronous state of power-grid networks is stable in disturbance attenuation. Finally, numerical simulations are provided to illustrate the effectiveness of the results by the IEEE 39 bus system.

  11. Structure identification and adaptive synchronization of uncertain general complex dynamical networks

    International Nuclear Information System (INIS)

    Xu Yuhua; Zhou Wuneng; Fang Jian'an; Lu Hongqian

    2009-01-01

    This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

  12. Structure identification and adaptive synchronization of uncertain general complex dynamical networks

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teacher' s College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Lu Hongqian [Shandong Institute of Light Industry, Shandong Jinan 250353 (China)

    2009-12-28

    This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

  13. Mean Square Synchronization of Stochastic Nonlinear Delayed Coupled Complex Networks

    Directory of Open Access Journals (Sweden)

    Chengrong Xie

    2013-01-01

    Full Text Available 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.

  14. Time Synchronization and Distribution Mechanisms for Space Networks

    Science.gov (United States)

    Woo, Simon S.; Gao, Jay L.; Clare, Loren P.; Mills, David L.

    2011-01-01

    This work discusses research on the problems of synchronizing and distributing time information between spacecraft based on the Network Time Protocol (NTP), where NTP is a standard time synchronization protocol widely used in the terrestrial network. The Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol was designed and developed for synchronizing spacecraft that are in proximity where proximity is less than 100,000 km distant. A particular application is synchronization between a Mars orbiter and rover. Lunar scenarios as well as outer-planet deep space mother-ship-probe missions may also apply. Spacecraft with more accurate time information functions as a time-server, and the other spacecraft functions as a time-client. PITS can be easily integrated and adaptable to the CCSDS Proximity-1 Space Link Protocol with minor modifications. In particular, PITS can take advantage of the timestamping strategy that underlying link layer functionality provides for accurate time offset calculation. The PITS algorithm achieves time synchronization with eight consecutive space network time packet exchanges between two spacecraft. PITS can detect and avoid possible errors from receiving duplicate and out-of-order packets by comparing with the current state variables and timestamps. Further, PITS is able to detect error events and autonomously recover from unexpected events that can possibly occur during the time synchronization and distribution process. This capability achieves an additional level of protocol protection on top of CRC or Error Correction Codes. PITS is a lightweight and efficient protocol, eliminating the needs for explicit frame sequence number and long buffer storage. The PITS protocol is capable of providing time synchronization and distribution services for a more general domain where multiple entities need to achieve time synchronization using a single point-to-point link.

  15. Synchronous Ethernet- Considerations and Implementation of the Packet Network Management Scheme

    Science.gov (United States)

    Gundale, A. S.; Aradhye, Ashwini

    2010-11-01

    Packet technologies were designed to work in asynchronous mode, where the oscillators in the equipment are free running. Although this allows the underlying infrastructure to operate, many applications exist that require frequency synchronization. Also, the ability to distribute synchronization from center to edge of network declines as infrastructure evolves toward a packet-based architecture. Synchronous Ethernet (SyncE) is a key development of the evolution of Ethernet into a carrier grade technology suitable for the WAN environment where frequency synchronization is required. The time of the day distribution in synchronized network at the physical layer enables many useful propositions in packet handling policies and other network management aspects.

  16. Exponential synchronization of complex networks with nonidentical time-delayed dynamical nodes

    International Nuclear Information System (INIS)

    Cai Shuiming; He Qinbin; Hao Junjun; Liu Zengrong

    2010-01-01

    In this Letter, exponential synchronization of a complex network with nonidentical time-delayed dynamical nodes is considered. Two effective control schemes are proposed to drive the network to synchronize globally exponentially onto any smooth goal dynamics. By applying open-loop control to all nodes and adding some intermittent controllers to partial nodes, some simple criteria for exponential synchronization of such network are established. Meanwhile, a pinning scheme deciding which nodes need to be pinned and a simply approximate formula for estimating the least number of pinned nodes are also provided. By introducing impulsive effects to the open-loop controlled network, another synchronization scheme is developed for the network with nonidentical time-delayed dynamical nodes, and an estimate of the upper bound of impulsive intervals ensuring global exponential stability of the synchronization process is also given. Numerical simulations are presented finally to demonstrate the effectiveness of the theoretical results.

  17. Synchronization of coupled chaotic dynamics on networks

    Indian Academy of Sciences (India)

    We review some recent work on the synchronization of coupled dynamical systems on a variety of networks. When nodes show synchronized behaviour, two interesting phenomena can be observed. First, there are some nodes of the floating type that show intermittent behaviour between getting attached to some clusters ...

  18. Stochastic synchronization of coupled neural networks with intermittent control

    International Nuclear Information System (INIS)

    Yang Xinsong; Cao Jinde

    2009-01-01

    In this Letter, we study the exponential stochastic synchronization problem for coupled neural networks with stochastic noise perturbations. Based on Lyapunov stability theory, inequality techniques, the properties of Weiner process, and adding different intermittent controllers, several sufficient conditions are obtained to ensure exponential stochastic synchronization of coupled neural networks with or without coupling delays under stochastic perturbations. These stochastic synchronization criteria are expressed in terms of several lower-dimensional linear matrix inequalities (LMIs) and can be easily verified. Moreover, the results of this Letter are applicable to both directed and undirected weighted networks. A numerical example and its simulations are offered to show the effectiveness of our new results.

  19. Measure of robustness for complex networks

    Science.gov (United States)

    Youssef, Mina Nabil

    Critical infrastructures are repeatedly attacked by external triggers causing tremendous amount of damages. Any infrastructure can be studied using the powerful theory of complex networks. A complex network is composed of extremely large number of different elements that exchange commodities providing significant services. The main functions of complex networks can be damaged by different types of attacks and failures that degrade the network performance. These attacks and failures are considered as disturbing dynamics, such as the spread of viruses in computer networks, the spread of epidemics in social networks, and the cascading failures in power grids. Depending on the network structure and the attack strength, every network differently suffers damages and performance degradation. Hence, quantifying the robustness of complex networks becomes an essential task. In this dissertation, new metrics are introduced to measure the robustness of technological and social networks with respect to the spread of epidemics, and the robustness of power grids with respect to cascading failures. First, we introduce a new metric called the Viral Conductance (VCSIS ) to assess the robustness of networks with respect to the spread of epidemics that are modeled through the susceptible/infected/susceptible (SIS) epidemic approach. In contrast to assessing the robustness of networks based on a classical metric, the epidemic threshold, the new metric integrates the fraction of infected nodes at steady state for all possible effective infection strengths. Through examples, VCSIS provides more insights about the robustness of networks than the epidemic threshold. In addition, both the paradoxical robustness of Barabasi-Albert preferential attachment networks and the effect of the topology on the steady state infection are studied, to show the importance of quantifying the robustness of networks. Second, a new metric VCSIR is introduced to assess the robustness of networks with respect

  20. Adaptive exponential synchronization of delayed neural networks with reaction-diffusion terms

    International Nuclear Information System (INIS)

    Sheng Li; Yang Huizhong; Lou Xuyang

    2009-01-01

    This paper presents an exponential synchronization scheme for a class of neural networks with time-varying and distributed delays and reaction-diffusion terms. An adaptive synchronization controller is derived to achieve the exponential synchronization of the drive-response structure of neural networks by using the Lyapunov stability theory. At the same time, the update laws of parameters are proposed to guarantee the synchronization of delayed neural networks with all parameters unknown. It is shown that the approaches developed here extend and improve the ideas presented in recent literatures.

  1. Robust and Low-Complexity Timing Synchronization Algorithm and its Architecture for ADSRC Applications

    Directory of Open Access Journals (Sweden)

    KIM, J.

    2009-10-01

    Full Text Available 5.9 GHz advanced dedicated short range communications (ADSRC is a short-to-medium range communication standard that supports both public safety and private operations in roadside-to-vehicle and vehicle-to-vehicle communication environments. The core technology of physical layer in ADSRC is orthogonal frequency division multiplexing (OFDM, which is sensitive to timing synchronization error. In this paper, a robust and low-complexity timing synchronization algorithm suitable for ADSRC system and its efficient hardware architecture are proposed. The implementation of the proposed architecture is performed with Xilinx Vertex-II XC2V1000 Field Programmable Gate Array (FPGA. The proposed algorithm is based on cross-correlation technique, which is employed to detect the starting point of short training symbol and the guard interval of the long training symbol. Synchronization error rate (SER evaluation results and post-layout simulation results show that the proposed algorithm is efficient in high-mobility environments. The post-layout results of implementation demonstrate the robustness and low-complexity of the proposed architecture.

  2. Synchronization of uncertain time-varying network based on sliding mode control technique

    Science.gov (United States)

    Lü, Ling; Li, Chengren; Bai, Suyuan; Li, Gang; Rong, Tingting; Gao, Yan; Yan, Zhe

    2017-09-01

    We research synchronization of uncertain time-varying network based on sliding mode control technique. The sliding mode control technique is first modified so that it can be applied to network synchronization. Further, by choosing the appropriate sliding surface, the identification law of uncertain parameter, the adaptive law of the time-varying coupling matrix element and the control input of network are designed, it is sure that the uncertain time-varying network can synchronize effectively the synchronization target. At last, we perform some numerical simulations to demonstrate the effectiveness of the proposed results.

  3. Synchronization analysis of coloured delayed networks under ...

    Indian Academy of Sciences (India)

    This paper investigates synchronization of coloured delayed networks under decentralized pinning intermittent control. To begin with, the time delays are taken into account in the coloured networks. In addition, we propose a decentralized pinning intermittent control for coloured delayed networks, which is different from that ...

  4. Perturbation analysis of complete synchronization in networks of phase oscillators.

    Science.gov (United States)

    Tönjes, Ralf; Blasius, Bernd

    2009-08-01

    The behavior of weakly coupled self-sustained oscillators can often be well described by phase equations. Here we use the paradigm of Kuramoto phase oscillators which are coupled in a network to calculate first- and second-order corrections to the frequency of the fully synchronized state for nonidentical oscillators. The topology of the underlying coupling network is reflected in the eigenvalues and eigenvectors of the network Laplacian which influence the synchronization frequency in a particular way. They characterize the importance of nodes in a network and the relations between them. Expected values for the synchronization frequency are obtained for oscillators with quenched random frequencies on a class of scale-free random networks and for a Erdös-Rényi random network. We briefly discuss an application of the perturbation theory in the second order to network structural analysis.

  5. Computer network time synchronization the network time protocol on earth and in space

    CERN Document Server

    Mills, David L

    2010-01-01

    Carefully coordinated, reliable, and accurate time synchronization is vital to a wide spectrum of fields-from air and ground traffic control, to buying and selling goods and services, to TV network programming. Ill-gotten time could even lead to the unimaginable and cause DNS caches to expire, leaving the entire Internet to implode on the root servers.Written by the original developer of the Network Time Protocol (NTP), Computer Network Time Synchronization: The Network Time Protocol on Earth and in Space, Second Edition addresses the technological infrastructure of time dissemination, distrib

  6. Information theory perspective on network robustness

    International Nuclear Information System (INIS)

    Schieber, Tiago A.; Carpi, Laura; Frery, Alejandro C.; Rosso, Osvaldo A.; Pardalos, Panos M.; Ravetti, Martín G.

    2016-01-01

    A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology. - Highlights: • A novel methodology to measure the robustness of a network to component failure or targeted attacks is proposed. • The use of the network's distance PDF allows a precise analysis. • The method provides a dynamic robustness profile showing the response of the topology to each failure event. • The measure is capable to detect network's critical elements.

  7. Chaotic Synchronization in Nearest-Neighbor Coupled Networks of 3D CNNs

    OpenAIRE

    Serrano-Guerrero, H.; Cruz-Hernández, C.; López-Gutiérrez, R.M.; Cardoza-Avendaño, L.; Chávez-Pérez, R.A.

    2013-01-01

    In this paper, a synchronization of Cellular Neural Networks (CNNs) in nearest-neighbor coupled arrays, is numerically studied. Synchronization of multiple chaotic CNNs is achieved by appealing to complex systems theory. In particular, we consider dynamical networks composed by 3D CNNs, as interconnected nodes, where the interactions in the networks are defined by coupling the first state of each node. Four cases of interest are considered: i) synchronization without chaotic master, ii) maste...

  8. Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling

    International Nuclear Information System (INIS)

    Jian-Rui, Chen; Li-Cheng, Jiao; Jian-She, Wu; Xiao-Hua, Wang

    2009-01-01

    A new general network model for two complex networks with time-varying delay coupling is presented. Then we investigate its synchronization phenomena. The two complex networks of the model differ in dynamic nodes, the number of nodes and the coupling connections. By using adaptive controllers, a synchronization criterion is derived. Numerical examples are given to demonstrate the effectiveness of the obtained synchronization criterion. This study may widen the application range of synchronization, such as in chaotic secure communication. (general)

  9. Synchronization of chaotic neural networks via output or state coupling

    International Nuclear Information System (INIS)

    Lu Hongtao; Leeuwen, C. van

    2006-01-01

    We consider the problem of global exponential synchronization between two identical chaotic neural networks that are linearly and unidirectionally coupled. We formulate a general framework for the synchronization problem in which one chaotic neural network, working as the driving system (or master), sends its output or state values to the other, which serves as the response system (or slave). We use Lyapunov functions to establish general theoretical conditions for designing the coupling matrix. Neither symmetry nor negative (positive) definiteness of the coupling matrix are required; under less restrictive conditions, the two coupled chaotic neural networks can achieve global exponential synchronization regardless of their initial states. Detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws

  10. Exponential Synchronization of Networked Chaotic Delayed Neural Network by a Hybrid Event Trigger Scheme.

    Science.gov (United States)

    Fei, Zhongyang; Guan, Chaoxu; Gao, Huijun; Zhongyang Fei; Chaoxu Guan; Huijun Gao; Fei, Zhongyang; Guan, Chaoxu; Gao, Huijun

    2018-06-01

    This paper is concerned with the exponential synchronization for master-slave chaotic delayed neural network with event trigger control scheme. The model is established on a network control framework, where both external disturbance and network-induced delay are taken into consideration. The desired aim is to synchronize the master and slave systems with limited communication capacity and network bandwidth. In order to save the network resource, we adopt a hybrid event trigger approach, which not only reduces the data package sending out, but also gets rid of the Zeno phenomenon. By using an appropriate Lyapunov functional, a sufficient criterion for the stability is proposed for the error system with extended ( , , )-dissipativity performance index. Moreover, hybrid event trigger scheme and controller are codesigned for network-based delayed neural network to guarantee the exponential synchronization between the master and slave systems. The effectiveness and potential of the proposed results are demonstrated through a numerical example.

  11. One- and two-cluster synchronized dynamics of non-diffusively coupled Tchebycheff map networks

    International Nuclear Information System (INIS)

    Schäfer, Mirko; Greiner, Martin

    2012-01-01

    We use the master stability formalism to discuss one- and two-cluster synchronization of coupled Tchebycheff map networks. For diffusively coupled map systems, the one-cluster synchronized dynamics is given by the behaviour of the individual maps, and the coupling only determines the stability of the coherent state. For the case of non-diffusive coupling and for two-cluster synchronization, the synchronized dynamics on networks is different from the behaviour of the single individual map. Depending on the coupling, we study numerically the characteristics of various forms of the resulting synchronized dynamics. The stability properties of the respective one-cluster synchronized states are discussed for arbitrary network structures. For the case of two-cluster synchronization on bipartite networks we also present analytical expressions for fixed points and zig-zag patterns, and explicitly determine the linear stability of these orbits for the special case of ring-networks.

  12. Detection of generalized synchronization using echo state networks

    OpenAIRE

    Ibáñez-Soria, D.; García Ojalvo, Jordi; Soria Frisch, Aureli; Ruffini, G.

    2018-01-01

    Generalized synchronization between coupled dynamical systems is a phenomenon of relevance in applications that range from secure communications to physiological modelling. Here, we test the capabilities of reservoir computing and, in particular, echo state networks for the detection of generalized synchronization. A nonlinear dynamical system consisting of two coupled Rössler chaotic attractors is used to generate temporal series consisting of time-locked generalized synchronized sequences i...

  13. Time synchronization of a wired sensor network for structural health monitoring

    International Nuclear Information System (INIS)

    Ishikawa, Ken-ichiro; Mita, Akira

    2008-01-01

    This paper introduces a time synchronization system for wired smart sensor networks to be applied to the structural health monitoring of gigantic structures. The jitter of sensor nodes in the wired network depends on the wire length between the origin and the destination of the time synchronization signals. The proposed system can theoretically achieve the accuracy to limit the jitter of sensors within 34 ns by adjusting the timing depending on the wire length, and experimentally showed the jitter of 190 m separation to be within 25 ns. The proposed system uses local area network (LAN) cables and does not require additional cabling for synchronization. Thus the proposed synchronization system can be embedded in the sensor network with minimal cost

  14. Synchronization challenges in packet-based Cloud-RAN fronthaul for mobile networks

    DEFF Research Database (Denmark)

    Checko, Aleksandra; Juul, Anders Christian; Christiansen, Henrik Lehrmann

    2015-01-01

    In this paper, we look at reusing existing packet-based network (e.g. Ethernet) to possibly decrease deployment costs of fronthaul Cloud Radio Access Network (C-RAN) network and cost of Baseband Unit (BBU) resources. The challenge of this solution is that it requires mobile traffic (until now...... transmitted over synchronous protocols) to traverse the asynchronous Ethernet without losing synchronization. We analyze synchronization requirements of mobile networks and present an overview of solutions that fulfill them in traditional mobile networks. Then we elaborate on challenges that packet-based...... fronthaul imposes. We analyze possible contributions to frequency and phase error. We verify the feasibility of using the IEEE 1588v2 also know as Precision Time Protocol (PTP) for providing accurate phase and frequency synchronization. The study is based on simulations made in OPNET modeler. Thereby we...

  15. Exponentially asymptotical synchronization in uncertain complex dynamical networks with time delay

    Energy Technology Data Exchange (ETDEWEB)

    Luo Qun; Yang Han; Li Lixiang; Yang Yixian [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Han Jiangxue, E-mail: luoqun@bupt.edu.c [National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China)

    2010-12-10

    Over the past decade, complex dynamical network synchronization has attracted more and more attention and important developments have been made. In this paper, we explore the scheme of globally exponentially asymptotical synchronization in complex dynamical networks with time delay. Based on Lyapunov stability theory and through defining the error function between adjacent nodes, four novel adaptive controllers are designed under four situations where the Lipschitz constants of the state function in nodes are known or unknown and the network structure is certain or uncertain, respectively. These controllers could not only globally asymptotically synchronize all nodes in networks, but also ensure that the error functions do not exceed the pre-scheduled exponential function. Finally, simulations of the synchronization among the chaotic system in the small-world and scale-free network structures are presented, which prove the effectiveness and feasibility of our controllers.

  16. Connectivities and synchronous firing in cortical neuronal networks

    International Nuclear Information System (INIS)

    Jia, L.C.; Sano, M.; Lai, P.-Y.; Chan, C.K.

    2004-01-01

    Network connectivities (k-bar) of cortical neural cultures are studied by synchronized firing and determined from measured correlations between fluorescence intensities of firing neurons. The bursting frequency (f) during synchronized firing of the networks is found to be an increasing function of k-bar. With f taken to be proportional to k-bar, a simple random model with a k-bar dependent connection probability p(k-bar) has been constructed to explain our experimental findings successfully

  17. IPTV inter-destination synchronization: A network-based approach

    NARCIS (Netherlands)

    Stokking, H.M.; Deventer, M.O. van; Niamut, O.A.; Walraven, F.A.; Mekuria, R.N.

    2010-01-01

    This paper introduces a novel network-based approach to inter-destination media synchronization. The approach meets the need for synchronization in advanced TV concepts like social TV and offers high scalability, unlike conventional end-point based approaches. The solution for interdestination media

  18. Structure Identification of Uncertain Complex Networks Based on Anticipatory Projective Synchronization.

    Directory of Open Access Journals (Sweden)

    Liu Heng

    Full Text Available This paper investigates a method to identify uncertain system parameters and unknown topological structure in general complex networks with or without time delay. A complex network, which has uncertain topology and unknown parameters, is designed as a drive network, and a known response complex network with an input controller is designed to identify the drive network. Under the proposed input controller, the drive network and the response network can achieve anticipatory projective synchronization when the system is steady. Lyapunov theorem and Barbǎlat's lemma guarantee the stability of synchronization manifold between two networks. When the synchronization is achieved, the system parameters and topology in response network can be changed to equal with the parameters and topology in drive network. A numerical example is given to show the effectiveness of the proposed method.

  19. Phase-response curves and synchronized neural networks.

    Science.gov (United States)

    Smeal, Roy M; Ermentrout, G Bard; White, John A

    2010-08-12

    We review the principal assumptions underlying the application of phase-response curves (PRCs) to synchronization in neuronal networks. The PRC measures how much a given synaptic input perturbs spike timing in a neural oscillator. Among other applications, PRCs make explicit predictions about whether a given network of interconnected neurons will synchronize, as is often observed in cortical structures. Regarding the assumptions of the PRC theory, we conclude: (i) The assumption of noise-tolerant cellular oscillations at or near the network frequency holds in some but not all cases. (ii) Reduced models for PRC-based analysis can be formally related to more realistic models. (iii) Spike-rate adaptation limits PRC-based analysis but does not invalidate it. (iv) The dependence of PRCs on synaptic location emphasizes the importance of improving methods of synaptic stimulation. (v) New methods can distinguish between oscillations that derive from mutual connections and those arising from common drive. (vi) It is helpful to assume linear summation of effects of synaptic inputs; experiments with trains of inputs call this assumption into question. (vii) Relatively subtle changes in network structure can invalidate PRC-based predictions. (viii) Heterogeneity in the preferred frequencies of component neurons does not invalidate PRC analysis, but can annihilate synchronous activity.

  20. Pinning synchronization of memristor-based neural networks with time-varying delays.

    Science.gov (United States)

    Yang, Zhanyu; Luo, Biao; Liu, Derong; Li, Yueheng

    2017-09-01

    In this paper, the synchronization of memristor-based neural networks with time-varying delays via pinning control is investigated. A novel pinning method is introduced to synchronize two memristor-based neural networks which denote drive system and response system, respectively. The dynamics are studied by theories of differential inclusions and nonsmooth analysis. In addition, some sufficient conditions are derived to guarantee asymptotic synchronization and exponential synchronization of memristor-based neural networks via the presented pinning control. Furthermore, some improvements about the proposed control method are also discussed in this paper. Finally, the effectiveness of the obtained results is demonstrated by numerical simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Power quality improvement of single-phase photovoltaic systems through a robust synchronization method

    DEFF Research Database (Denmark)

    Hadjidemetriou, Lenos; Kyriakides, Elias; Yang, Yongheng

    2014-01-01

    An increasing amount of single-phase photovoltaic (PV) systems on the distribution network requires more advanced synchronization methods in order to meet the grid codes with respect to power quality and fault ride through capability. The response of the synchronization technique selected...... is crucial for the performance of PV inverters. In this paper, a new synchronization method with good dynamics and accurate response under highly distorted voltage is proposed. This method uses a Multi-Harmonic Decoupling Cell (MHDC), which cancels out the oscillations on the synchronization signals due...

  2. Structure-function relationship in complex brain networks expressed by hierarchical synchronization

    International Nuclear Information System (INIS)

    Zhou Changsong; Zemanova, Lucia; Zamora-Lopez, Gorka; Hilgetag, Claus C; Kurths, Juergen

    2007-01-01

    The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks

  3. Structure-function relationship in complex brain networks expressed by hierarchical synchronization

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Changsong [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zemanova, Lucia [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zamora-Lopez, Gorka [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Hilgetag, Claus C [Jacobs University Bremen, Campus Ring 6, Rm 116, D-28759 Bremen (Germany); Kurths, Juergen [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany)

    2007-06-15

    The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.

  4. Autapse-induced synchronization in a coupled neuronal network

    International Nuclear Information System (INIS)

    Ma, Jun; Song, Xinlin; Jin, Wuyin; Wang, Chuni

    2015-01-01

    Highlights: • The functional effect of autapse on neuronal activity is detected. • Autapse driving plays active role in regulating electrical activities as pacemaker. • It confirms biological experimental results for rhythm synchronization between heterogeneous cells. - Abstract: The effect of autapse on coupled neuronal network is detected. In our studies, three identical neurons are connected with ring type and autapse connected to one neuron of the network. The autapse connected to neuron can impose time-delayed feedback in close loop on the neuron thus the dynamics of membrane potentials can be changed. Firstly, the effect of autapse driving on single neuron is confirmed that negative feedback can calm down the neuronal activity while positive feedback can excite the neuronal activity. Secondly, the collective electrical behaviors of neurons are regulated by a pacemaker, which associated with the autapse forcing. By using appropriate gain and time delay in the autapse, the neurons can reach synchronization and the membrane potentials of all neurons can oscillate with the same rhythm under mutual coupling. It indicates that autapse forcing plays an important role in changing the collective electric activities of neuronal network, and appropriate electric modes can be selected due to the switch of feedback type(positive or negative) in autapse. And the autapse-induced synchronization in network is also consistent with some biological experiments about synchronization between nonidentical neurons.

  5. Emergence of robustness in networks of networks

    Science.gov (United States)

    Roth, Kevin; Morone, Flaviano; Min, Byungjoon; Makse, Hernán A.

    2017-06-01

    A model of interdependent networks of networks (NONs) was introduced recently [Proc. Natl. Acad. Sci. (USA) 114, 3849 (2017), 10.1073/pnas.1620808114] in the context of brain activation to identify the neural collective influencers in the brain NON. Here we investigate the emergence of robustness in such a model, and we develop an approach to derive an exact expression for the random percolation transition in Erdös-Rényi NONs of this kind. Analytical calculations are in agreement with numerical simulations, and highlight the robustness of the NON against random node failures, which thus presents a new robust universality class of NONs. The key aspect of this robust NON model is that a node can be activated even if it does not belong to the giant mutually connected component, thus allowing the NON to be built from below the percolation threshold, which is not possible in previous models of interdependent networks. Interestingly, the phase diagram of the model unveils particular patterns of interconnectivity for which the NON is most vulnerable, thereby marking the boundary above which the robustness of the system improves with increasing dependency connections.

  6. The formation of synchronization cliques during the development of modular neural networks

    International Nuclear Information System (INIS)

    Fuchs, Einat; Ayali, Amir; Ben-Jacob, Eshel; Boccaletti, Stefano

    2009-01-01

    Modular organization is a special feature shared by many biological and social networks alike. It is a hallmark for systems exhibiting multitasking, in which individual tasks are performed by separated and yet coordinated functional groups. Understanding how networks of segregated modules develop to support coordinated multitasking functionalities is the main topic of the current study. Using simulations of biologically inspired neuronal networks during development, we study the formation of functional groups (cliques) and inter-neuronal synchronization. The results indicate that synchronization cliques first develop locally according to the explicit network topological organization. Later on, at intermediate connectivity levels, when networks have both local segregation and long-range integration, new synchronization cliques with distinctive properties are formed. In particular, by defining a new measure of synchronization centrality, we identify at these developmental stages dominant neurons whose functional centrality largely exceeds the topological one. These are generated mainly in a few dominant clusters that become the centers of the newly formed synchronization cliques. We show that by the local synchronization properties at the very early developmental stages, it is possible to predict with high accuracy which clusters will become dominant in later stages of network development

  7. Cluster synchronization for directed community networks via pinning partial schemes

    International Nuclear Information System (INIS)

    Hu Cheng; Jiang Haijun

    2012-01-01

    Highlights: ► Cluster synchronization for directed community networks is proposed by pinning partial schemes. ► Each community is considered as a whole. ► Several novel pinning criteria are derived based on the information of communities. ► A numerical example with simulation is provided. - Abstract: In this paper, we focus on driving a class of directed networks to achieve cluster synchronization by pinning schemes. The desired cluster synchronization states are no longer decoupled orbits but a set of un-decoupled trajectories. Each community is considered as a whole and the synchronization criteria are derived based on the information of communities. Several pinning schemes including feedback control and adaptive strategy are proposed to select controlled communities by analyzing the information of each community such as indegrees and outdegrees. In all, this paper answers several challenging problems in pinning control of directed community networks: (1) What communities should be chosen as controlled candidates? (2) How many communities are needed to be controlled? (3) How large should the control gains be used in a given community network to achieve cluster synchronization? Finally, an example with numerical simulations is given to demonstrate the effectiveness of the theoretical results.

  8. Synchronization of cellular neural networks of neutral type via dynamic feedback controller

    International Nuclear Information System (INIS)

    Park, Ju H.

    2009-01-01

    In this paper, we aim to study global synchronization for neural networks with neutral delay. A dynamic feedback control scheme is proposed to achieve the synchronization between drive network and response network. By utilizing the Lyapunov function and linear matrix inequalities (LMIs), we derive simple and efficient criterion in terms of LMIs for synchronization. The feedback controllers can be easily obtained by solving the derived LMIs.

  9. Multiple synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses

    International Nuclear Information System (INIS)

    Liu, Chen; Wang, Jiang; Wang, Lin; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok

    2014-01-01

    Highlights: • Synchronization transitions in hybrid scale-free neuronal networks are investigated. • Multiple synchronization transitions can be induced by the time delay. • Effect of synchronization transitions depends on the ratio of the electrical and chemical synapses. • Coupling strength and the density of inter-neuronal links can enhance the synchronization. -- Abstract: The impacts of information transmission delay on the synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses are investigated. Numerical results show that multiple appearances of synchronization regions transitions can be induced by different information transmission delays. With the time delay increasing, the synchronization of neuronal activities can be enhanced or destroyed, irrespective of the probability of chemical synapses in the whole hybrid neuronal network. In particular, for larger probability of electrical synapses, the regions of synchronous activities appear broader with stronger synchronization ability of electrical synapses compared with chemical ones. Moreover, it can be found that increasing the coupling strength can promote synchronization monotonously, playing the similar role of the increasing the probability of the electrical synapses. Interestingly, the structures and parameters of the scale-free neuronal networks, especially the structural evolvement plays a more subtle role in the synchronization transitions. In the network formation process, it is found that every new vertex is attached to the more old vertices already present in the network, the more synchronous activities will be emerge

  10. Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme

    Science.gov (United States)

    Khanzadeh, Alireza; Pourgholi, Mahdi

    2016-08-01

    In the conventional chaos synchronization methods, the time at which two chaotic systems are synchronized, is usually unknown and depends on initial conditions. In this work based on Lyapunov stability theory a sliding mode controller with time-varying switching surfaces is proposed to achieve chaos synchronization at a pre-specified time for the first time. The proposed controller is able to synchronize chaotic systems precisely at any time when we want. Moreover, by choosing the time-varying switching surfaces in a way that the reaching phase is eliminated, the synchronization becomes robust to uncertainties and exogenous disturbances. Simulation results are presented to show the effectiveness of the proposed method of stabilizing and synchronizing chaotic systems with complete robustness to uncertainty and disturbances exactly at a pre-specified time.

  11. Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme

    International Nuclear Information System (INIS)

    Khanzadeh, Alireza; Pourgholi, Mahdi

    2016-01-01

    In the conventional chaos synchronization methods, the time at which two chaotic systems are synchronized, is usually unknown and depends on initial conditions. In this work based on Lyapunov stability theory a sliding mode controller with time-varying switching surfaces is proposed to achieve chaos synchronization at a pre-specified time for the first time. The proposed controller is able to synchronize chaotic systems precisely at any time when we want. Moreover, by choosing the time-varying switching surfaces in a way that the reaching phase is eliminated, the synchronization becomes robust to uncertainties and exogenous disturbances. Simulation results are presented to show the effectiveness of the proposed method of stabilizing and synchronizing chaotic systems with complete robustness to uncertainty and disturbances exactly at a pre-specified time. (paper)

  12. Generalized Mutual Synchronization between Two Controlled Interdependent Networks

    Directory of Open Access Journals (Sweden)

    Quan Xu

    2014-01-01

    Full Text Available This paper mainly focuses on the generalized mutual synchronization between two controlled interdependent networks. First, we propose the general model of controlled interdependent networks A and B with time-varying internetwork delays coupling. Then, by constructing Lyapunov functions and utilizing adaptive control technique, some sufficient conditions are established to ensure that the mutual synchronization errors between the state variables of networks A and B can asymptotically converge to zero. Finally, two numerical examples are given to illustrate the effectiveness of the theoretical results and to explore potential application in future smart grid. The simulation results also show how interdependent topologies and internetwork coupling delays influence the mutual synchronizability, which help to design interdependent networks with optimal mutual synchronizability.

  13. Pinning adaptive synchronization of a class of uncertain complex dynamical networks with multi-link against network deterioration

    International Nuclear Information System (INIS)

    Li, Lixiang; Li, Weiwei; Kurths, Jürgen; Luo, Qun; Yang, Yixian; Li, Shudong

    2015-01-01

    For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method

  14. Fast sparsely synchronized brain rhythms in a scale-free neural network.

    Science.gov (United States)

    Kim, Sang-Yoon; Lim, Woochang

    2015-08-01

    We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D. For small D, full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp>〈fi〉 (〈fi〉: ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4〈fi〉 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For Dsynchronization emerges in the whole population because the spatial correlation length between the neuronal pairs covers the whole system. Furthermore, the degree of population synchronization is also measured in terms of two types of realistic statistical-mechanical measures. Only for the partial and sparse synchronization do contributions of individual neuronal dynamics to population synchronization change depending on their degrees, unlike in the case of full synchronization. Consequently, dynamics of individual neurons reveal the inhomogeneous network structure for the case of partial and sparse synchronization, which is in contrast to the case of

  15. Fast sparsely synchronized brain rhythms in a scale-free neural network

    Science.gov (United States)

    Kim, Sang-Yoon; Lim, Woochang

    2015-08-01

    We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D . For small D , full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp> ( : ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For D synchronization emerges in the whole population because the spatial correlation length between the neuronal pairs covers the whole system. Furthermore, the degree of population synchronization is also measured in terms of two types of realistic statistical-mechanical measures. Only for the partial and sparse synchronization do contributions of individual neuronal dynamics to population synchronization change depending on their degrees, unlike in the case of full synchronization. Consequently, dynamics of individual neurons reveal the inhomogeneous network structure for the case of partial and sparse synchronization, which is in contrast to the case of statistically homogeneous

  16. Robust Exponential Synchronization for a Class of Master-Slave Distributed Parameter Systems with Spatially Variable Coefficients and Nonlinear Perturbation

    Directory of Open Access Journals (Sweden)

    Chengdong Yang

    2015-01-01

    Full Text Available This paper addresses the exponential synchronization problem of a class of master-slave distributed parameter systems (DPSs with spatially variable coefficients and spatiotemporally variable nonlinear perturbation, modeled by a couple of semilinear parabolic partial differential equations (PDEs. With a locally Lipschitz constraint, the perturbation is a continuous function of time, space, and system state. Firstly, a sufficient condition for the robust exponential synchronization of the unforced semilinear master-slave PDE systems is investigated for all admissible nonlinear perturbations. Secondly, a robust distributed proportional-spatial derivative (P-sD state feedback controller is desired such that the closed-loop master-slave PDE systems achieve exponential synchronization. Using Lyapunov’s direct method and the technique of integration by parts, the main results of this paper are presented in terms of spatial differential linear matrix inequalities (SDLMIs. Finally, two numerical examples are provided to show the effectiveness of the proposed methods applied to the robust exponential synchronization problem of master-slave PDE systems with nonlinear perturbation.

  17. The role of leadership in the synchronization of directed complex networks

    International Nuclear Information System (INIS)

    Sheshbolouki, Aida; Zarei, Mina; Sarbazi-Azad, Hamid

    2015-01-01

    Synchronization is a phenomenon that occurs in systems of interacting units, and is widespread in nature, society and technology. Recent studies have enlightened us regarding the interplay between synchronization dynamics and interaction structure. However, most of these studies neglect that real-world networks may actually be directed and disconnected. Here, we study the synchronization of directed networks with multiple leaders using the Kuramoto model. We found that in networks with high driving strength, the steady-state frequency of each node is determined by the linear combination of leaders’ natural frequencies, with structural coefficients that can be calculated using the eigenvectors of a network Laplacian matrix corresponding to zero eigenvalues. The steady-state frequencies of the nodes following multiple leaders are not fixed and have sharp peaks between consecutive time instances where leaders meet each other in the phase circle. The results suggest a new way of understanding how leadership style influences the synchronization dynamics of directed networks. (paper)

  18. Bursting synchronization in scale-free networks

    International Nuclear Information System (INIS)

    Batista, C.A.S.; Batista, A.M.; Pontes, J.C.A. de; Lopes, S.R.; Viana, R.L.

    2009-01-01

    Neuronal networks in some areas of the brain cortex present the scale-free property, i.e., the neuron connectivity is distributed according to a power-law, such that neurons are more likely to couple with other already well-connected ones. Neuron activity presents two timescales, a fast one related to action-potential spiking, and a slow timescale in which bursting takes place. Some pathological conditions are related with the synchronization of the bursting activity in a weak sense, meaning the adjustment of the bursting phase due to coupling. Hence it has been proposed that an externally applied time-periodic signal be applied in order to control undesirable synchronized bursting rhythms. We investigated this kind of intervention using a two-dimensional map to describe neurons with spiking-bursting activity in a scale-free network.

  19. Hierarchical-control-based output synchronization of coexisting attractor networks

    International Nuclear Information System (INIS)

    Yun-Zhong, Song; Yi-Fa, Tang

    2010-01-01

    This paper introduces the concept of hierarchical-control-based output synchronization of coexisting attractor networks. Within the new framework, each dynamic node is made passive at first utilizing intra-control around its own arena. Then each dynamic node is viewed as one agent, and on account of that, the solution of output synchronization of coexisting attractor networks is transformed into a multi-agent consensus problem, which is made possible by virtue of local interaction between individual neighbours; this distributed working way of coordination is coined as inter-control, which is only specified by the topological structure of the network. Provided that the network is connected and balanced, the output synchronization would come true naturally via synergy between intra and inter-control actions, where the Tightness is proved theoretically via convex composite Lyapunov functions. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme. (general)

  20. Synchronization criteria for generalized reaction-diffusion neural networks via periodically intermittent control.

    Science.gov (United States)

    Gan, Qintao; Lv, Tianshi; Fu, Zhenhua

    2016-04-01

    In this paper, the synchronization problem for a class of generalized neural networks with time-varying delays and reaction-diffusion terms is investigated concerning Neumann boundary conditions in terms of p-norm. The proposed generalized neural networks model includes reaction-diffusion local field neural networks and reaction-diffusion static neural networks as its special cases. By establishing a new inequality, some simple and useful conditions are obtained analytically to guarantee the global exponential synchronization of the addressed neural networks under the periodically intermittent control. According to the theoretical results, the influences of diffusion coefficients, diffusion space, and control rate on synchronization are analyzed. Finally, the feasibility and effectiveness of the proposed methods are shown by simulation examples, and by choosing different diffusion coefficients, diffusion spaces, and control rates, different controlled synchronization states can be obtained.

  1. Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model

    Directory of Open Access Journals (Sweden)

    Ying Du

    2014-01-01

    Full Text Available This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. From ISI plots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. The ISI-distance is used to measure the noise effects on spike trains quantitatively. It is found that spike trains observed in neural models can be more strongly affected by noise for different temperatures in some aspects; meanwhile, spike train has greater variability with the noise intensity increasing. The synchronization of neuronal network with different connectivity patterns is also studied. It is shown that chaotic and high period patterns are more difficult to get complete synchronization than the situation in single spike and low period patterns. The neuronal network will exhibit various patterns of firing synchronization by varying some key parameters such as the coupling strength. Different types of firing synchronization are diagnosed by a correlation coefficient and the ISI-distance method. The simulations show that the synchronization status of neurons is related to the network connectivity patterns.

  2. Quasi-projective synchronization of fractional-order complex-valued recurrent neural networks.

    Science.gov (United States)

    Yang, Shuai; Yu, Juan; Hu, Cheng; Jiang, Haijun

    2018-08-01

    In this paper, without separating the complex-valued neural networks into two real-valued systems, the quasi-projective synchronization of fractional-order complex-valued neural networks is investigated. First, two new fractional-order inequalities are established by using the theory of complex functions, Laplace transform and Mittag-Leffler functions, which generalize traditional inequalities with the first-order derivative in the real domain. Additionally, different from hybrid control schemes given in the previous work concerning the projective synchronization, a simple and linear control strategy is designed in this paper and several criteria are derived to ensure quasi-projective synchronization of the complex-valued neural networks with fractional-order based on the established fractional-order inequalities and the theory of complex functions. Moreover, the error bounds of quasi-projective synchronization are estimated. Especially, some conditions are also presented for the Mittag-Leffler synchronization of the addressed neural networks. Finally, some numerical examples with simulations are provided to show the effectiveness of the derived theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. The influence of single neuron dynamics and network topology on time delay-induced multiple synchronous behaviors in inhibitory coupled network

    International Nuclear Information System (INIS)

    Zhao, Zhiguo; Gu, Huaguang

    2015-01-01

    Highlights: • Time delay-induced multiple synchronous behaviors was simulated in neuronal networks. • Multiple behaviors appear at time delays shorter than a bursting period of neurons. • The more spikes per burst of bursting, the more synchronous regions of time delay. • From regular to random via small-world networks, synchronous degree becomes weak. • An interpretation of the multiple behaviors and the influence of network are provided. - Abstract: Time delay induced-multiple synchronous behaviors are simulated in neuronal network composed of many inhibitory neurons and appear at different time delays shorter than a period of endogenous bursting of individual neurons. It is different from previous investigations wherein only one of multiple synchronous behaviors appears at time delay shorter than a period of endogenous firing and others appear at time delay longer than the period duration. The bursting patterns of the synchronous behaviors are identified based on the dynamics of an individual neuron stimulated by a signal similar to the inhibitory coupling current, which is applied at the decaying branch of a spike and suitable phase within the quiescent state of the endogenous bursting. If a burst of endogenous bursting contains more spikes, the synchronous behaviors appear at more regions of time delay. As the coupling strength increases, the multiple synchronous behaviors appear in a sequence because the different threshold of coupling current or strength is needed to achieve synchronous behaviors. From regular, to small-world, and to random networks, synchronous degree of the multiple synchronous behaviors becomes weak, and synchronous bursting patterns with lower spikes per burst disappear, which is properly interpreted by the difference of coupling current between neurons induced by different degree and the high threshold of coupling current to achieve synchronization for the absent synchronous bursting patterns. The results of the influence of

  4. Robust synchronization of master-slave chaotic systems using approximate model: An experimental study.

    Science.gov (United States)

    Ahmed, Hafiz; Salgado, Ivan; Ríos, Héctor

    2018-02-01

    Robust synchronization of master slave chaotic systems are considered in this work. First an approximate model of the error system is obtained using the ultra-local model concept. Then a Continuous Singular Terminal Sliding-Mode (CSTSM) Controller is designed for the purpose of synchronization. The proposed approach is output feedback-based and uses fixed-time higher order sliding-mode (HOSM) differentiator for state estimation. Numerical simulation and experimental results are given to show the effectiveness of the proposed technique. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Pinning impulsive synchronization of stochastic delayed coupled networks

    International Nuclear Information System (INIS)

    Tang Yang; Fang Jian-An; Wong W K; Miao Qing-Ying

    2011-01-01

    In this paper, the pinning synchronization problem of stochastic delayed complex network (SDCN) is investigated by using a novel hybrid pinning controller. The proposed hybrid pinning controller is composed of adaptive controller and impulsive controller, where the two controllers are both added to a fraction of nodes in the network. Using the Lyapunov stability theory and the novel hybrid pinning controller, some sufficient conditions are derived for the exponential synchronization of such dynamical networks in mean square. Two numerical simulation examples are provided to verify the effectiveness of the proposed approach. The simulation results show that the proposed control scheme has a fast convergence rate compared with the conventional adaptive pinning method. (general)

  6. Synchronization and secure communication of chaotic systems via robust adaptive high-gain fuzzy observer

    International Nuclear Information System (INIS)

    Hyun, Chang-Ho; Park, Chang-Woo; Kim, Jae-Hun; Park, Mignon

    2009-01-01

    This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization and secure communication of chaotic systems. It is assumed that their states are immeasurable and their parameters are unknown. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. It improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived to estimate the unknown parameters and the stability of the proposed observer is analyzed. Some simulation result of synchronization and secure communication of chaotic systems is given to present the validity of theoretical derivations and the performance of the proposed observer as an application.

  7. Network synchronization in a population of star-coupled fractional nonlinear oscillators

    Energy Technology Data Exchange (ETDEWEB)

    Wang Junwei, E-mail: wangjunweilj@yahoo.com.c [School of Informatics, Guangdong University of Foreign Studies, Guangzhou 510006 (China); Zhang Yanbin [School of Computer Science, Hangzhou Dianzi University, Hangzhou 310018 (China)

    2010-03-29

    The topic of fractional calculus is enjoying growing interest among mathematicians, physicists and engineers in recent years. For complex network consisting of more than two fractional-order systems, however, it is difficult to establish its synchronization behavior. In this Letter, we study the synchronized motions in a star network of coupled fractional-order systems in which the major element is coupled to each of the noninteracting individual elements. On the basis of the stability theory of linear fractional-order differential equations, we derive a sufficient condition for the stability of the synchronization behavior in such a network. Furthermore, we verify our theoretical results by numerical simulations of star-coupled network with fractional-order chaotic nodes.

  8. Robust-yet-fragile nature of interdependent networks

    Science.gov (United States)

    Tan, Fei; Xia, Yongxiang; Wei, Zhi

    2015-05-01

    Interdependent networks have been shown to be extremely vulnerable based on the percolation model. Parshani et al. [Europhys. Lett. 92, 68002 (2010), 10.1209/0295-5075/92/68002] further indicated that the more intersimilar networks are, the more robust they are to random failures. When traffic load is considered, how do the coupling patterns impact cascading failures in interdependent networks? This question has been largely unexplored until now. In this paper, we address this question by investigating the robustness of interdependent Erdös-Rényi random graphs and Barabási-Albert scale-free networks under either random failures or intentional attacks. It is found that interdependent Erdös-Rényi random graphs are robust yet fragile under either random failures or intentional attacks. Interdependent Barabási-Albert scale-free networks, however, are only robust yet fragile under random failures but fragile under intentional attacks. We further analyze the interdependent communication network and power grid and achieve similar results. These results advance our understanding of how interdependency shapes network robustness.

  9. Adaptive approach to global synchronization of directed networks with fast switching topologies

    International Nuclear Information System (INIS)

    Qin Buzhi; Lu Xinbiao

    2010-01-01

    Global synchronization of directed networks with switching topologies is investigated. It is found that if there exists at least one directed spanning tree in the network with the fixed time-average topology and the time-average topology is achieved sufficiently fast, the network will reach global synchronization for appreciate coupling strength. Furthermore, this appreciate coupling strength may be obtained by local adaptive approach. A sufficient condition about the global synchronization is given. Numerical simulations verify the effectiveness of the adaptive strategy.

  10. Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks.

    Science.gov (United States)

    Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming

    2017-01-01

    In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections.

  11. Synchronizations in small-world networks of spiking neurons: Diffusive versus sigmoid couplings

    International Nuclear Information System (INIS)

    Hasegawa, Hideo

    2005-01-01

    By using a semianalytical dynamical mean-field approximation previously proposed by the author [H. Hasegawa, Phys. Rev. E 70, 066107 (2004)], we have studied the synchronization of stochastic, small-world (SW) networks of FitzHugh-Nagumo neurons with diffusive couplings. The difference and similarity between results for diffusive and sigmoid couplings have been discussed. It has been shown that with introducing the weak heterogeneity to regular networks, the synchronization may be slightly increased for diffusive couplings, while it is decreased for sigmoid couplings. This increase in the synchronization for diffusive couplings is shown to be due to their local, negative feedback contributions, but not due to the short average distance in SW networks. Synchronization of SW networks depends not only on their structure but also on the type of couplings

  12. Bandwidth Efficient Hybrid Synchronization for Wireless Sensor Network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Prasad, Neeli R.; Prasad, Ramjee

    2015-01-01

    Data collection and transmission are the fundamental operations of Wireless Sensor Networks (WSNs). A key challenge in effective data collection and transmission is to schedule and synchronize the activities of the nodes with the global clock. This paper proposes the Bandwidth Efficient Hybrid...... in the network and then perform the pair-wise synchronization. With the mobility of node, the structure frequently changes causing an increase in energy consumption. To mitigate the problem BESDA aggregate data with the notion of a global timescale throughout the network and schedule based time-division multiple...... accesses (TDMA) techniques as MAC layer protocol. It reduces the collision of packets. Simulation results show that BESDA is energy efficient, with increased throughput, and has less delay as compared with state-of-the-art....

  13. Testing a Firefly-Inspired Synchronization Algorithm in a Complex Wireless Sensor Network.

    Science.gov (United States)

    Hao, Chuangbo; Song, Ping; Yang, Cheng; Liu, Xiongjun

    2017-03-08

    Data acquisition is the foundation of soft sensor and data fusion. Distributed data acquisition and its synchronization are the important technologies to ensure the accuracy of soft sensors. As a research topic in bionic science, the firefly-inspired algorithm has attracted widespread attention as a new synchronization method. Aiming at reducing the design difficulty of firefly-inspired synchronization algorithms for Wireless Sensor Networks (WSNs) with complex topologies, this paper presents a firefly-inspired synchronization algorithm based on a multiscale discrete phase model that can optimize the performance tradeoff between the network scalability and synchronization capability in a complex wireless sensor network. The synchronization process can be regarded as a Markov state transition, which ensures the stability of this algorithm. Compared with the Miroll and Steven model and Reachback Firefly Algorithm, the proposed algorithm obtains better stability and performance. Finally, its practicality has been experimentally confirmed using 30 nodes in a real multi-hop topology with low quality links.

  14. Outer synchronization between two different fractional-order general complex dynamical networks

    International Nuclear Information System (INIS)

    Xiang-Jun, Wu; Hong-Tao, Lu

    2010-01-01

    Outer synchronization between two different fractional-order general complex dynamical networks is investigated in this paper. Based on the stability theory of the fractional-order system, the sufficient criteria for outer synchronization are derived analytically by applying the nonlinear control and the bidirectional coupling methods. The proposed synchronization method is applicable to almost all kinds of coupled fractional-order general complex dynamical networks. Neither a symmetric nor irreducible coupling configuration matrix is required. In addition, no constraint is imposed on the inner-coupling matrix. Numerical examples are also provided to demonstrate the validity of the presented synchronization scheme. Numeric evidence shows that both the feedback strength k and the fractional order α can be chosen appropriately to adjust the synchronization effect effectively. (general)

  15. Synchronization of Switched Neural Networks With Communication Delays via the Event-Triggered Control.

    Science.gov (United States)

    Wen, Shiping; Zeng, Zhigang; Chen, Michael Z Q; Huang, Tingwen

    2017-10-01

    This paper addresses the issue of synchronization of switched delayed neural networks with communication delays via event-triggered control. For synchronizing coupled switched neural networks, we propose a novel event-triggered control law which could greatly reduce the number of control updates for synchronization tasks of coupled switched neural networks involving embedded microprocessors with limited on-board resources. The control signals are driven by properly defined events, which depend on the measurement errors and current-sampled states. By using a delay system method, a novel model of synchronization error system with delays is proposed with the communication delays and event-triggered control in the unified framework for coupled switched neural networks. The criteria are derived for the event-triggered synchronization analysis and control synthesis of switched neural networks via the Lyapunov-Krasovskii functional method and free weighting matrix approach. A numerical example is elaborated on to illustrate the effectiveness of the derived results.

  16. Pinning synchronization of hybrid-coupled directed delayed dynamical network via intermittent control.

    Science.gov (United States)

    Cai, Shuiming; Zhou, Peipei; Liu, Zengrong

    2014-09-01

    This paper concerns the problem of exponential synchronization for a class of general delayed dynamical networks with hybrid coupling via pinning periodically intermittent control. Both the internal delay and coupling delay are taken into account in the network model. Meanwhile, the transmission delay and self-feedback delay are involved in the delayed coupling term. By establishing a new differential inequality, several simple and useful exponential synchronization criteria are derived analytically. It is shown that the controlled synchronization state can vary in comparison with the conventional synchronized solution, and the degree of the node and the inner delayed coupling matrix play important roles in the controlled synchronization state. By choosing different inner delayed coupling matrices and the degrees of the node, different controlled synchronization states can be obtained. Furthermore, the detail pinning schemes deciding what nodes should be chosen as pinned candidates and how many nodes are needed to be pinned for a fixed coupling strength are provided. The simple procedures illuminating how to design suitable intermittent controllers in real application are also given. Numerical simulations, including an undirected scale-free network and a directed small-world network, are finally presented to demonstrate the effectiveness of the theoretical results.

  17. Impact of delays on the synchronization transitions of modular neuronal networks with hybrid synapses

    Science.gov (United States)

    Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok

    2013-09-01

    The combined effects of the information transmission delay and the ratio of the electrical and chemical synapses on the synchronization transitions in the hybrid modular neuronal network are investigated in this paper. Numerical results show that the synchronization of neuron activities can be either promoted or destroyed as the information transmission delay increases, irrespective of the probability of electrical synapses in the hybrid-synaptic network. Interestingly, when the number of the electrical synapses exceeds a certain level, further increasing its proportion can obviously enhance the spatiotemporal synchronization transitions. Moreover, the coupling strength has a significant effect on the synchronization transition. The dominated type of the synapse always has a more profound effect on the emergency of the synchronous behaviors. Furthermore, the results of the modular neuronal network structures demonstrate that excessive partitioning of the modular network may result in the dramatic detriment of neuronal synchronization. Considering that information transmission delays are inevitable in intra- and inter-neuronal networks communication, the obtained results may have important implications for the exploration of the synchronization mechanism underlying several neural system diseases such as Parkinson's Disease.

  18. Synchronization dynamics in a small pacemaker neuronal ensemble via a robust adaptive controller

    International Nuclear Information System (INIS)

    Cornejo-Pérez, O.; Solis-Perales, G.C.; Arenas-Prado, J.A.

    2012-01-01

    The synchronization dynamics of a pacemaker neuronal ensemble under the action of a control command is studied herein. The ensemble corresponds to the pyloric central pattern generator of the stomatogastric ganglion of lobster. The desired dynamics is provided by means of an external master neuron and it is induced via a nonlinear controller. Such a controller is composed of a linearizing-like controller and a high gain observer; the controller is able to counteract uncertainties and external perturbations in the controlled system. Numerical simulations of the robust synchronization dynamics of the master neuron and the pacemaker neuronal ensemble are displayed.

  19. On common noise-induced synchronization in complex networks with state-dependent noise diffusion processes

    Science.gov (United States)

    Russo, Giovanni; Shorten, Robert

    2018-04-01

    This paper is concerned with the study of common noise-induced synchronization phenomena in complex networks of diffusively coupled nonlinear systems. We consider the case where common noise propagation depends on the network state and, as a result, the noise diffusion process at the nodes depends on the state of the network. For such networks, we present an algebraic sufficient condition for the onset of synchronization, which depends on the network topology, the dynamics at the nodes, the coupling strength and the noise diffusion. Our result explicitly shows that certain noise diffusion processes can drive an unsynchronized network towards synchronization. In order to illustrate the effectiveness of our result, we consider two applications: collective decision processes and synchronization of chaotic systems. We explicitly show that, in the former application, a sufficiently large noise can drive a population towards a common decision, while, in the latter, we show how common noise can synchronize a network of Lorentz chaotic systems.

  20. DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks.

    Science.gov (United States)

    Zhou, Feng; Wang, Qi; Nie, DongHu; Qiao, Gang

    2018-05-25

    Time synchronization is the foundation of cooperative work among nodes of underwater sensor networks; it takes a critical role in the research and application of underwater sensor networks. Although numerous time synchronization protocols have been proposed for terrestrial wireless sensor networks, they cannot be directly applied to underwater sensor networks. This is because most of them typically assume that the propagation delay among sensor nodes is negligible, which is not the case in underwater sensor networks. Time synchronization is mainly affected by a long propagation delay among sensor nodes due to the low propagation speed of acoustic signals. Furthermore, sensor nodes in underwater tend to experience some degree of mobility due to wind or ocean current, or some other nodes are on self-propelled vehicles, such as autonomous underwater vehicles (AUVs). In this paper, we propose a Doppler-enhanced time synchronization scheme for mobile underwater sensor networks, called DE-Sync. Our new scheme considers the effect of the clock skew during the process of estimating the Doppler scale factor and directly substitutes the Doppler scale factor into linear regression to achieve the estimation of the clock skew and offset. Simulation results show that DE-Sync outperforms existing time synchronization protocols in both accuracy and energy efficiency.

  1. Mutational robustness of gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Aalt D J van Dijk

    Full Text Available Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor-target gene interactions but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive. In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence.

  2. Explosive transitions to synchronization in networks of phase oscillators.

    Science.gov (United States)

    Leyva, I; Navas, A; Sendiña-Nadal, I; Almendral, J A; Buldú, J M; Zanin, M; Papo, D; Boccaletti, S

    2013-01-01

    The emergence of dynamical abrupt transitions in the macroscopic state of a system is currently a subject of the utmost interest. The occurrence of a first-order phase transition to synchronization of an ensemble of networked phase oscillators was reported, so far, for very particular network architectures. Here, we show how a sharp, discontinuous transition can occur, instead, as a generic feature of networks of phase oscillators. Precisely, we set conditions for the transition from unsynchronized to synchronized states to be first-order, and demonstrate how these conditions can be attained in a very wide spectrum of situations. We then show how the occurrence of such transitions is always accompanied by the spontaneous setting of frequency-degree correlation features. Third, we show that the conditions for abrupt transitions can be even softened in several cases. Finally, we discuss, as a possible application, the use of this phenomenon to express magnetic-like states of synchronization.

  3. Nonlinear transfer function encodes synchronization in a neural network from the mammalian brain.

    Science.gov (United States)

    Menendez de la Prida, L; Sanchez-Andres, J V

    1999-09-01

    Synchronization is one of the mechanisms by which the brain encodes information. The observed synchronization of neuronal activity has, however, several levels of fluctuations, which presumably regulate local features of specific areas. This means that biological neural networks should have an intrinsic mechanism able to synchronize the neuronal activity but also to preserve the firing capability of individual cells. Here, we investigate the input-output relationship of a biological neural network from developing mammalian brain, i.e., the hippocampus. We show that the probability of occurrence of synchronous output activity (which consists in stereotyped population bursts recorded throughout the hippocampus) is encoded by a sigmoidal transfer function of the input frequency. Under this scope, low-frequency inputs will not produce any coherent output while high-frequency inputs will determine a synchronous pattern of output activity (population bursts). We analyze the effect of the network size (N) on the parameters of the transfer function (threshold and slope). We found that sigmoidal functions realistically simulate the synchronous output activity of hippocampal neural networks. This outcome is particularly important in the application of results from neural network models to neurobiology.

  4. Adaptive Synchronization of Fractional Order Complex-Variable Dynamical Networks via Pinning Control

    Science.gov (United States)

    Ding, Da-Wei; Yan, Jie; Wang, Nian; Liang, Dong

    2017-09-01

    In this paper, the synchronization of fractional order complex-variable dynamical networks is studied using an adaptive pinning control strategy based on close center degree. Some effective criteria for global synchronization of fractional order complex-variable dynamical networks are derived based on the Lyapunov stability theory. From the theoretical analysis, one concludes that under appropriate conditions, the complex-variable dynamical networks can realize the global synchronization by using the proper adaptive pinning control method. Meanwhile, we succeed in solving the problem about how much coupling strength should be applied to ensure the synchronization of the fractional order complex networks. Therefore, compared with the existing results, the synchronization method in this paper is more general and convenient. This result extends the synchronization condition of the real-variable dynamical networks to the complex-valued field, which makes our research more practical. Finally, two simulation examples show that the derived theoretical results are valid and the proposed adaptive pinning method is effective. Supported by National Natural Science Foundation of China under Grant No. 61201227, National Natural Science Foundation of China Guangdong Joint Fund under Grant No. U1201255, the Natural Science Foundation of Anhui Province under Grant No. 1208085MF93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B, and also supported by Chinese Scholarship Council

  5. Graph properties of synchronized cortical networks during visual working memory maintenance.

    Science.gov (United States)

    Palva, Satu; Monto, Simo; Palva, J Matias

    2010-02-15

    Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.

  6. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    NARCIS (Netherlands)

    Hjorth, J.J.J.; Dawitz, J.; Kroon, T.; da Silva Dias Pires, J.H.; Dassen, V.J.; Berkhout, J.A.; Emperador Melero, J.; Nadadhur, A.G.; Alevra, M.; Toonen, R.F.G.; Heine, V.M.; Mansvelder, H.D.; Meredith, R.M.

    2016-01-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell

  7. Adaptive control of dynamical synchronization on evolving networks with noise disturbances

    Science.gov (United States)

    Yuan, Wu-Jie; Zhou, Jian-Fang; Sendiña-Nadal, Irene; Boccaletti, Stefano; Wang, Zhen

    2018-02-01

    In real-world networked systems, the underlying structure is often affected by external and internal unforeseen factors, making its evolution typically inaccessible. An adaptive strategy was introduced for maintaining synchronization on unpredictably evolving networks [Sorrentino and Ott, Phys. Rev. Lett. 100, 114101 (2008), 10.1103/PhysRevLett.100.114101], which yet does not consider the noise disturbances widely existing in networks' environments. We provide here strategies to control dynamical synchronization on slowly and unpredictably evolving networks subjected to noise disturbances which are observed at the node and at the communication channel level. With our strategy, the nodes' coupling strength is adaptively adjusted with the aim of controlling synchronization, and according only to their received signal and noise disturbances. We first provide a theoretical analysis of the control scheme by introducing an error potential function to seek for the minimization of the synchronization error. Then, we show numerical experiments which verify our theoretical results. In particular, it is found that our adaptive strategy is effective even for the case in which the dynamics of the uncontrolled network would be explosive (i.e., the states of all the nodes would diverge to infinity).

  8. Adaptative synchronization in multi-output fractional-order complex dynamical networks and secure communications

    Science.gov (United States)

    Mata-Machuca, Juan L.; Aguilar-López, Ricardo

    2018-01-01

    This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.

  9. Finite time synchronization of memristor-based Cohen-Grossberg neural networks with mixed delays

    OpenAIRE

    Chen, Chuan; Li, Lixiang; Peng, Haipeng; Yang, Yixian

    2017-01-01

    Finite time synchronization, which means synchronization can be achieved in a settling time, is desirable in some practical applications. However, most of the published results on finite time synchronization don't include delays or only include discrete delays. In view of the fact that distributed delays inevitably exist in neural networks, this paper aims to investigate the finite time synchronization of memristor-based Cohen-Grossberg neural networks (MCGNNs) with both discrete delay and di...

  10. Robustness Envelopes of Networks

    NARCIS (Netherlands)

    Trajanovski, S.; Martín-Hernández, J.; Winterbach, W.; Van Mieghem, P.

    2013-01-01

    We study the robustness of networks under node removal, considering random node failure, as well as targeted node attacks based on network centrality measures. Whilst both of these have been studied in the literature, existing approaches tend to study random failure in terms of average-case

  11. Counterpart synchronization of duplex networks with delayed nodes and noise perturbation

    International Nuclear Information System (INIS)

    Wei, Xiang; Wu, Xiaoqun; Lu, Jun-an; Zhao, Junchan

    2015-01-01

    In the real world, many complex systems are represented not by single networks but rather by sets of interdependent ones. In these specific networks, nodes in one network mutually interact with nodes in other networks. This paper focuses on a simple representative case of two-layer networks (the so-called duplex networks) with unidirectional inter-layer couplings. That is, each node in one network depends on a counterpart in the other network. Accordingly, the former network is called the response layer and the latter network is the drive layer. Specifically, synchronization between each node in the drive layer and its counterpart in the response layer (counterpart synchronization (CS)) in these kinds of duplex networks with delayed nodes and noise perturbation is investigated. Based on the LaSalle-type invariance principle, a control technique is proposed and a sufficient condition is developed for realizing CS of duplex networks. Furthermore, two corollaries are derived as special cases. In addition, node dynamics within each layer can be varied and topologies of the two layers are not necessarily identical. Therefore, the proposed synchronization method can be applied to a wide range of multiplex networks. Numerical examples are provided to illustrate the feasibility and effectiveness of the results. (paper)

  12. Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

    International Nuclear Information System (INIS)

    Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

    2013-01-01

    This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network

  13. Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

    Science.gov (United States)

    Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

    2013-12-01

    This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.

  14. O(t-α)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations.

    Science.gov (United States)

    Chen, Jiejie; Chen, Boshan; Zeng, Zhigang

    2018-04-01

    This paper investigates O(t -α )-synchronization and adaptive Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations. Firstly, based on the framework of Filippov solution and differential inclusion theory, using a Razumikhin-type method, some sufficient conditions ensuring the global O(t -α )-synchronization of considered networks are established via a linear-type discontinuous control. Next, a new fractional differential inequality is established and two new discontinuous adaptive controller is designed to achieve Mittag-Leffler synchronization between the drive system and the response systems using this inequality. Finally, two numerical simulations are given to show the effectiveness of the theoretical results. Our approach and theoretical results have a leading significance in the design of synchronized fractional-order memristive neural networks circuits involving discontinuous activations and time-varying delays. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Coarse graining for synchronization in directed networks

    Science.gov (United States)

    Zeng, An; Lü, Linyuan

    2011-05-01

    Coarse-graining model is a promising way to analyze and visualize large-scale networks. The coarse-grained networks are required to preserve statistical properties as well as the dynamic behaviors of the initial networks. Some methods have been proposed and found effective in undirected networks, while the study on coarse-graining directed networks lacks of consideration. In this paper we proposed a path-based coarse-graining (PCG) method to coarse grain the directed networks. Performing the linear stability analysis of synchronization and numerical simulation of the Kuramoto model on four kinds of directed networks, including tree networks and variants of Barabási-Albert networks, Watts-Strogatz networks, and Erdös-Rényi networks, we find our method can effectively preserve the network synchronizability.

  16. Globally exponential synchronization in an array of asymmetric coupled neural networks

    International Nuclear Information System (INIS)

    Lu Jianquan; Ho, Daniel W.C.; Liu Ming

    2007-01-01

    In this Letter, we study the globally exponential synchronization in an array of linearly coupled neural networks with delayed coupling. The coupling configuration matrix is assumed to be asymmetric, which is more coincident with the real-world network. The difficulty arising from the asymmetry of the coupling matrix has been overcame in this work. Some synchronization criteria are given in terms of strict linear matrix inequalities (LMIs), which can be efficiently solved by using interior point algorithm. Some previous synchronization results are generalized. Numerical simulation is also given to verify our theoretical analysis

  17. Sliding mode synchronization controller design with neural network for uncertain chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Mou Chen [College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China)], E-mail: chenmou@nuaa.edu.cn; Jiang Changsheng; Bin Jiang; Wu Qingxian [College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China)

    2009-02-28

    A sliding mode synchronization controller is presented with RBF neural network for two chaotic systems in this paper. The compound disturbance of the synchronization error system consists of nonlinear uncertainties and exterior disturbances of chaotic systems. Based on RBF neural networks, a compound disturbance observer is proposed and the update law of parameters is given to monitor the compound disturbance. The synchronization controller is given based on the output of the compound disturbance observer. The designed controller can make the synchronization error convergent to zero and overcome the disruption of the uncertainty and the exterior disturbance of the system. Finally, an example is given to demonstrate the availability of the proposed synchronization control method.

  18. Robustness of airline alliance route networks

    Science.gov (United States)

    Lordan, Oriol; Sallan, Jose M.; Simo, Pep; Gonzalez-Prieto, David

    2015-05-01

    The aim of this study is to analyze the robustness of the three major airline alliances' (i.e., Star Alliance, oneworld and SkyTeam) route networks. Firstly, the normalization of a multi-scale measure of vulnerability is proposed in order to perform the analysis in networks with different sizes, i.e., number of nodes. An alternative node selection criterion is also proposed in order to study robustness and vulnerability of such complex networks, based on network efficiency. And lastly, a new procedure - the inverted adaptive strategy - is presented to sort the nodes in order to anticipate network breakdown. Finally, the robustness of the three alliance networks are analyzed with (1) a normalized multi-scale measure of vulnerability, (2) an adaptive strategy based on four different criteria and (3) an inverted adaptive strategy based on the efficiency criterion. The results show that Star Alliance has the most resilient route network, followed by SkyTeam and then oneworld. It was also shown that the inverted adaptive strategy based on the efficiency criterion - inverted efficiency - shows a great success in quickly breaking networks similar to that found with betweenness criterion but with even better results.

  19. Firefly Clock Synchronization in an 802.15.4 Wireless Network

    Directory of Open Access Journals (Sweden)

    Elmenreich Wilfried

    2009-01-01

    Full Text Available This paper describes the design and implementation of a distributed self-stabilizing clock synchronization algorithm based on the biological example of Asian Fireflies. Huge swarms of these fireflies use the principle of pulse coupled oscillators in order to synchronously emit light flashes to attract mating partners. When applying this algorithm to real sensor networks, typically, nodes cannot receive messages while transmitting, which prevents the networked nodes from reaching synchronization. In order to counteract this deafness problem, we adopt a variant of the Reachback Firefly Algorithm to distribute the timing of light flashes in a given time window without affecting the quality of the synchronization. A case study implemented on 802.15.4 Zigbee nodes presents the application of this approach for a time-triggered communication scheduling and coordinated duty cycling in order to enhance the battery lifetime of the nodes.

  20. An Energy-efficient Clock Synchronization Protocol for Wireless Sensor Networks

    OpenAIRE

    Albu, Roxana; Labit, Yann; Thierry, Gayraud; Pascal, Berthou

    2010-01-01

    5p.; International audience; The behavior of Wireless Sensor Networks (WSN) is nowadays widely analyzed. One of the most important issues is related to their energy consumption, as this has a major impact on the network lifetime. Another important application requirement is to ensure data sensing synchronization, which leads to additional energy consumption as a high number of messages is sent and received at each node. Our proposal consists in implementing a combined synchronization protocol...

  1. Synchronization of Integrated Systems on a Chip

    Directory of Open Access Journals (Sweden)

    González-Díaz O.

    2012-04-01

    Full Text Available In the present paper, the non-conventional interconnected and coupled ring oscillators approach working as clock distribution networks to synchronize electronic systems on a chip (SoC is proposed. Typical CMOS (Complementary Metal-Oxide Semiconductor N-well 0.35 µm Austria Micro Systems process parameters were used for conventional and non-conventional clock distribution nets design and simulation. Experimental results from local and global clock distribution networks fabricated using a CMOS 0.35 µm process show that the use of interconnected rings arrays, as globally asynchronous locally synchronous (GALS clock distribution networks, represent an appropriate approach due to good performance regarding scalability, low clock-skew, high-speed, faults tolerant and robust under process variations, regularity, and modularity.

  2. Exponential networked synchronization of master-slave chaotic systems with time-varying communication topologies

    International Nuclear Information System (INIS)

    Yang Dong-Sheng; Liu Zhen-Wei; Liu Zhao-Bing; Zhao Yan

    2012-01-01

    The networked synchronization problem of a class of master-slave chaotic systems with time-varying communication topologies is investigated in this paper. Based on algebraic graph theory and matrix theory, a simple linear state feedback controller is designed to synchronize the master chaotic system and the slave chaotic systems with a time-varying communication topology connection. The exponential stability of the closed-loop networked synchronization error system is guaranteed by applying Lyapunov stability theory. The derived novel criteria are in the form of linear matrix inequalities (LMIs), which are easy to examine and tremendously reduce the computation burden from the feedback matrices. This paper provides an alternative networked secure communication scheme which can be extended conveniently. An illustrative example is given to demonstrate the effectiveness of the proposed networked synchronization method. (general)

  3. Selective control of vortex polarities by microwave field in two robustly synchronized spin-torque nano-oscillators

    Science.gov (United States)

    Li, Yi; de Milly, Xavier; Klein, Olivier; Cros, Vincent; Grollier, Julie; de Loubens, Grégoire

    2018-01-01

    Manipulating operation states of coupled spin-torque nano-oscillators (STNOs), including their synchronization, is essential for applications such as complex oscillator networks. In this work, we experimentally demonstrate selective control of two coupled vortex STNOs through microwave-assisted switching of their vortex core polarities. First, the two oscillators are shown to synchronize due to the dipolar interaction in a broad frequency range tuned by an external biasing field. Coherent output is demonstrated along with strong linewidth reduction. Then, we show individual vortex polarity control of each oscillator, which leads to synchronization/desynchronization due to accompanied frequency shift. Our methods can be easily extended to multiple-element coupled oscillator networks.

  4. Novel approaches to pin cluster synchronization on complex dynamical networks in Lur'e forms

    Science.gov (United States)

    Tang, Ze; Park, Ju H.; Feng, Jianwen

    2018-04-01

    This paper investigates the cluster synchronization of complex dynamical networks consisted of identical or nonidentical Lur'e systems. Due to the special topology structure of the complex networks and the existence of stochastic perturbations, a kind of randomly occurring pinning controller is designed which not only synchronizes all Lur'e systems in the same cluster but also decreases the negative influence among different clusters. Firstly, based on an extended integral inequality, the convex combination theorem and S-procedure, the conditions for cluster synchronization of identical Lur'e networks are derived in a convex domain. Secondly, randomly occurring adaptive pinning controllers with two independent Bernoulli stochastic variables are designed and then sufficient conditions are obtained for the cluster synchronization on complex networks consisted of nonidentical Lur'e systems. In addition, suitable control gains for successful cluster synchronization of nonidentical Lur'e networks are acquired by designing some adaptive updating laws. Finally, we present two numerical examples to demonstrate the validity of the control scheme and the theoretical analysis.

  5. Enhancing Time Synchronization Support in Wireless Sensor Networks.

    Science.gov (United States)

    Tavares Bruscato, Leandro; Heimfarth, Tales; Pignaton de Freitas, Edison

    2017-12-20

    With the emerging Internet of Things (IoT) technology becoming reality, a number of applications are being proposed. Several of these applications are highly dependent on wireless sensor networks (WSN) to acquire data from the surrounding environment. In order to be really useful for most of applications, the acquired data must be coherent in terms of the time in which they are acquired, which implies that the entire sensor network presents a certain level of time synchronization. Moreover, to efficiently exchange and forward data, many communication protocols used in WSN rely also on time synchronization among the sensor nodes. Observing the importance in complying with this need for time synchronization, this work focuses on the second synchronization problem, proposing, implementing and testing a time synchronization service for low-power WSN using low frequency real-time clocks in each node. To implement this service, three algorithms based on different strategies are proposed: one based on an auto-correction approach, the second based on a prediction mechanism, while the third uses an analytical correction mechanism. Their goal is the same, i.e., to make the clocks of the sensor nodes converge as quickly as possible and then to keep them most similar as possible. This goal comes along with the requirement to keep low energy consumption. Differently from other works in the literature, the proposal here is independent of any specific protocol, i.e., it may be adapted to be used in different protocols. Moreover, it explores the minimum number of synchronization messages by means of a smart clock update strategy, allowing the trade-off between the desired level of synchronization and the associated energy consumption. Experimental results, which includes data acquired from simulations and testbed deployments, provide evidence of the success in meeting this goal, as well as providing means to compare these three approaches considering the best synchronization

  6. Enhancing Time Synchronization Support in Wireless Sensor Networks

    Science.gov (United States)

    Tavares Bruscato, Leandro; Heimfarth, Tales; Pignaton de Freitas, Edison

    2017-01-01

    With the emerging Internet of Things (IoT) technology becoming reality, a number of applications are being proposed. Several of these applications are highly dependent on wireless sensor networks (WSN) to acquire data from the surrounding environment. In order to be really useful for most of applications, the acquired data must be coherent in terms of the time in which they are acquired, which implies that the entire sensor network presents a certain level of time synchronization. Moreover, to efficiently exchange and forward data, many communication protocols used in WSN rely also on time synchronization among the sensor nodes. Observing the importance in complying with this need for time synchronization, this work focuses on the second synchronization problem, proposing, implementing and testing a time synchronization service for low-power WSN using low frequency real-time clocks in each node. To implement this service, three algorithms based on different strategies are proposed: one based on an auto-correction approach, the second based on a prediction mechanism, while the third uses an analytical correction mechanism. Their goal is the same, i.e., to make the clocks of the sensor nodes converge as quickly as possible and then to keep them most similar as possible. This goal comes along with the requirement to keep low energy consumption. Differently from other works in the literature, the proposal here is independent of any specific protocol, i.e., it may be adapted to be used in different protocols. Moreover, it explores the minimum number of synchronization messages by means of a smart clock update strategy, allowing the trade-off between the desired level of synchronization and the associated energy consumption. Experimental results, which includes data acquired from simulations and testbed deployments, provide evidence of the success in meeting this goal, as well as providing means to compare these three approaches considering the best synchronization

  7. Synchronization in a Random Length Ring Network for SDN-Controlled Optical TDM Switching

    DEFF Research Database (Denmark)

    Kamchevska, Valerija; Cristofori, Valentina; Da Ros, Francesco

    2016-01-01

    . In addition, we propose a novel synchronization algorithm that enables automatic synchronization of software defined networking controlled all-optical TDM switching nodes connected in a ring network. Besides providing synchronization, the algorithm also can facilitate dynamic slot size change and failure......In this paper we focus on optical time division multiplexed (TDM) switching and its main distinguishing characteristics compared with other optical subwavelength switching technologies. We review and discuss in detail the synchronization requirements that allow for proper switching operation...... detection. We experimentally validate the algorithm behavior and achieve correct operation for three different ring lengths. Moreover, we experimentally demonstrate data plane connectivity in a ring network composed of three nodes and show successful wavelength division multiplexing space division...

  8. Synchronization of Switched Interval Networks and Applications to Chaotic Neural Networks

    OpenAIRE

    Cao, Jinde; Alofi, Abdulaziz; Al-Mazrooei, Abdullah; Elaiw, Ahmed

    2013-01-01

    This paper investigates synchronization problem of switched delay networks with interval parameters uncertainty, based on the theories of the switched systems and drive-response technique, a mathematical model of the switched interval drive-response error system is established. Without constructing Lyapunov-Krasovskii functions, introducing matrix measure method for the first time to switched time-varying delay networks, combining Halanay inequality technique, synchroniza...

  9. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    Science.gov (United States)

    Hjorth, Johannes J J; Dawitz, Julia; Kroon, Tim; Pires, Johny; Dassen, Valerie J; Berkhout, Janna A; Emperador Melero, Javier; Nadadhur, Aish G; Alevra, Mihai; Toonen, Ruud F; Heine, Vivi M; Mansvelder, Huibert D; Meredith, Rhiannon M

    2016-04-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. © 2015 Wiley Periodicals, Inc.

  10. Adaptive synchronization of the complex dynamical network with non-derivative and derivative coupling

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teachers' College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Sun Wen [School of Mathematics and Information, Yangtze University, Hubei Jingzhou 434023 (China)

    2010-04-05

    This Letter investigates the synchronization of a general complex dynamical network with non-derivative and derivative coupling. Based on LaSalle's invariance principle, adaptive synchronization criteria are obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-derivative and derivative coupling can asymptotically synchronize to a given trajectory, and several useful criteria for synchronization are given. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulations results show the method is effective.

  11. Cluster synchronization of community network with distributed time delays via impulsive control

    International Nuclear Information System (INIS)

    Leng Hui; Wu Zhao-Yan

    2016-01-01

    Cluster synchronization is an important dynamical behavior in community networks and deserves further investigations. A community network with distributed time delays is investigated in this paper. For achieving cluster synchronization, an impulsive control scheme is introduced to design proper controllers and an adaptive strategy is adopted to make the impulsive controllers unified for different networks. Through taking advantage of the linear matrix inequality technique and constructing Lyapunov functions, some synchronization criteria with respect to the impulsive gains, instants, and system parameters without adaptive strategy are obtained and generalized to the adaptive case. Finally, numerical examples are presented to demonstrate the effectiveness of the theoretical results. (paper)

  12. Cluster synchronization transmission of different external signals in discrete uncertain network

    Science.gov (United States)

    Li, Chengren; Lü, Ling; Chen, Liansong; Hong, Yixuan; Zhou, Shuang; Yang, Yiming

    2018-07-01

    We research cluster synchronization transmissions of different external signals in discrete uncertain network. Based on the Lyapunov theorem, the network controller and the identification law of uncertain adjustment parameter are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain adjustment parameter. In our technical scheme, the network nodes in each cluster and the transmitted external signal can be different, and they allow the presence of uncertain parameters in the network. Especially, we are free to choose the clustering topologies, the cluster number and the node number in each cluster.

  13. Robust anti-synchronization of uncertain chaotic systems based on multiple-kernel least squares support vector machine modeling

    International Nuclear Information System (INIS)

    Chen Qiang; Ren Xuemei; Na Jing

    2011-01-01

    Highlights: Model uncertainty of the system is approximated by multiple-kernel LSSVM. Approximation errors and disturbances are compensated in the controller design. Asymptotical anti-synchronization is achieved with model uncertainty and disturbances. Abstract: In this paper, we propose a robust anti-synchronization scheme based on multiple-kernel least squares support vector machine (MK-LSSVM) modeling for two uncertain chaotic systems. The multiple-kernel regression, which is a linear combination of basic kernels, is designed to approximate system uncertainties by constructing a multiple-kernel Lagrangian function and computing the corresponding regression parameters. Then, a robust feedback control based on MK-LSSVM modeling is presented and an improved update law is employed to estimate the unknown bound of the approximation error. The proposed control scheme can guarantee the asymptotic convergence of the anti-synchronization errors in the presence of system uncertainties and external disturbances. Numerical examples are provided to show the effectiveness of the proposed method.

  14. Robust fractional-order proportional-integral observer for synchronization of chaotic fractional-order systems

    KAUST Repository

    N U+02BC Doye, Ibrahima

    2018-02-13

    In this paper, we propose a robust fractional-order proportional-integral U+0028 FOPI U+0029 observer for the synchronization of nonlinear fractional-order chaotic systems. The convergence of the observer is proved, and sufficient conditions are derived in terms of linear matrix inequalities U+0028 LMIs U+0029 approach by using an indirect Lyapunov method. The proposed U+0028 FOPI U+0029 observer is robust against Lipschitz additive nonlinear uncertainty. It is also compared to the fractional-order proportional U+0028 FOP U+0029 observer and its performance is illustrated through simulations done on the fractional-order chaotic Lorenz system.

  15. Robust fractional-order proportional-integral observer for synchronization of chaotic fractional-order systems

    KAUST Repository

    N U+02BC Doye, Ibrahima; Salama, Khaled N.; Laleg-Kirati, Taous-Meriem

    2018-01-01

    In this paper, we propose a robust fractional-order proportional-integral U+0028 FOPI U+0029 observer for the synchronization of nonlinear fractional-order chaotic systems. The convergence of the observer is proved, and sufficient conditions are derived in terms of linear matrix inequalities U+0028 LMIs U+0029 approach by using an indirect Lyapunov method. The proposed U+0028 FOPI U+0029 observer is robust against Lipschitz additive nonlinear uncertainty. It is also compared to the fractional-order proportional U+0028 FOP U+0029 observer and its performance is illustrated through simulations done on the fractional-order chaotic Lorenz system.

  16. Critical features of coupling parameter in synchronization of small world neural networks

    International Nuclear Information System (INIS)

    Li Yanlong; Ma Jun; Xu Wenke; Li Hongbo; Wu Min

    2008-01-01

    The critical features of a coupling parameter in the synchronization of small world neural networks are investigated. A power law decay form is observed in this spatially extended system, the larger linked degree becomes, the larger critical coupling intensity. There exists maximal and minimal critical coupling intensity for synchronization in the extended system. An approximate synchronization diagram has been constructed. In the case of partial coupling, a primary result is presented about the critical coupling fraction for various linked degree of networks

  17. Quantized Synchronization of Chaotic Neural Networks With Scheduled Output Feedback Control.

    Science.gov (United States)

    Wan, Ying; Cao, Jinde; Wen, Guanghui

    In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control

  18. Synchronization propensity in networks of dynamical systems: A purely topological indicator

    OpenAIRE

    Fasani, S.; Rinaldi, S.

    2012-01-01

    Synchronization in networks of identical dynamical systems is enhanced by the number of manifolds in which synchrony of groups of systems is conserved or reinforced. Since the number of these invariant manifolds depends only on the coupling architecture of the network, it can be proposed as a purely topological indicator of synchronization propensity. The proposal is empirically validated through the detailed study of an ecological application.

  19. System and method for time synchronization in a wireless network

    Science.gov (United States)

    Gonia, Patrick S.; Kolavennu, Soumitri N.; Mahasenan, Arun V.; Budampati, Ramakrishna S.

    2010-03-30

    A system includes multiple wireless nodes forming a cluster in a wireless network, where each wireless node is configured to communicate and exchange data wirelessly based on a clock. One of the wireless nodes is configured to operate as a cluster master. Each of the other wireless nodes is configured to (i) receive time synchronization information from a parent node, (ii) adjust its clock based on the received time synchronization information, and (iii) broadcast time synchronization information based on the time synchronization information received by that wireless node. The time synchronization information received by each of the other wireless nodes is based on time synchronization information provided by the cluster master so that the other wireless nodes substantially synchronize their clocks with the clock of the cluster master.

  20. Impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks.

    Science.gov (United States)

    Chen, Wu-Hua; Lu, Xiaomei; Zheng, Wei Xing

    2015-04-01

    This paper investigates the problems of impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks (DDNNs). Two types of DDNNs with stabilizing impulses are studied. By introducing the time-varying Lyapunov functional to capture the dynamical characteristics of discrete-time impulsive delayed neural networks (DIDNNs) and by using a convex combination technique, new exponential stability criteria are derived in terms of linear matrix inequalities. The stability criteria for DIDNNs are independent of the size of time delay but rely on the lengths of impulsive intervals. With the newly obtained stability results, sufficient conditions on the existence of linear-state feedback impulsive controllers are derived. Moreover, a novel impulsive synchronization scheme for two identical DDNNs is proposed. The novel impulsive synchronization scheme allows synchronizing two identical DDNNs with unknown delays. Simulation results are given to validate the effectiveness of the proposed criteria of impulsive stabilization and impulsive synchronization of DDNNs. Finally, an application of the obtained impulsive synchronization result for two identical chaotic DDNNs to a secure communication scheme is presented.

  1. Novel criteria for exponential synchronization of inner time-varying complex networks with coupling delay

    International Nuclear Information System (INIS)

    Zhang Qun-Jiao; Zhao Jun-Chan

    2012-01-01

    This paper mainly investigates the exponential synchronization of an inner time-varying complex network with coupling delay. Firstly, the synchronization of complex networks is decoupled into the stability of the corresponding dynamical systems. Based on the Lyapunov function theory, some sufficient conditions to guarantee its stability with any given convergence rate are derived, thus the synchronization of the networks is achieved. Finally, the results are illustrated by a simple time-varying network model with a coupling delay. All involved numerical simulations verify the correctness of the theoretical analysis. (general)

  2. Synchronization of chaotic recurrent neural networks with time-varying delays using nonlinear feedback control

    International Nuclear Information System (INIS)

    Cui Baotong; Lou Xuyang

    2009-01-01

    In this paper, a new method to synchronize two identical chaotic recurrent neural networks is proposed. Using the drive-response concept, a nonlinear feedback control law is derived to achieve the state synchronization of the two identical chaotic neural networks. Furthermore, based on the Lyapunov method, a delay independent sufficient synchronization condition in terms of linear matrix inequality (LMI) is obtained. A numerical example with graphical illustrations is given to illuminate the presented synchronization scheme

  3. Synchronization enhancement via an oscillatory bath in a network of ...

    Indian Academy of Sciences (India)

    2015-02-05

    Feb 5, 2015 ... 2Monell Chemical Senses Center, 3500 Market Street, Philadelphia, PA 19104, USA ... The robustness of synchronization strategy is tested using a local and global ..... enhancement effect that the oscillatory bath has in the ...

  4. An energy efficient and dynamic time synchronization protocol for wireless sensor networks

    Science.gov (United States)

    Zhang, Anran; Bai, Fengshan

    2017-01-01

    Time synchronization is an important support technology of WSN(Wireless Sensor Network), and plays an irreplaceable role in the development of WSN. In view of the disadvantage of the traditional timing sync protocol for sensor networks (TPSN), we present a Physical Timing-sync Protocol (PTPSN) that aims at reducing the energy consumption of the synchronization process and realizes a dynamic Network. The algorithm broadcasts reference message to select some nodes in specific area. The receiver calculate offset of every selected node, and then calculate the average of offset to compensate for clock skew . At the same time ,we add time-filter process to ensure the security of the algorithm for time synchronization. The experiment results show that our algorithm is efficient in both saving energy consumption and dynamic network, and it can effectively resist attacks.

  5. Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

    International Nuclear Information System (INIS)

    Hao Yinghang; Gong, Yubing; Wang Li; Ma Xiaoguang; Yang Chuanlu

    2011-01-01

    Research highlights: → Single synchronization transition for gap-junctional coupling. → Multiple synchronization transitions for chemical synaptic coupling. → Gap junctions and chemical synapses have different impacts on synchronization transition. → Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

  6. Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling

    Energy Technology Data Exchange (ETDEWEB)

    Hao Yinghang [School of Physics, Ludong University, Yantai 264025 (China); Gong, Yubing, E-mail: gongyubing09@hotmail.co [School of Physics, Ludong University, Yantai 264025 (China); Wang Li; Ma Xiaoguang; Yang Chuanlu [School of Physics, Ludong University, Yantai 264025 (China)

    2011-04-15

    Research highlights: Single synchronization transition for gap-junctional coupling. Multiple synchronization transitions for chemical synaptic coupling. Gap junctions and chemical synapses have different impacts on synchronization transition. Chemical synapses may play a dominant role in neurons' information processing. - Abstract: In this paper, we have studied time delay- and coupling strength-induced synchronization transitions in scale-free modified Hodgkin-Huxley (MHH) neuron networks with gap-junctions and chemical synaptic coupling. It is shown that the synchronization transitions are much different for these two coupling types. For gap-junctions, the neurons exhibit a single synchronization transition with time delay and coupling strength, while for chemical synapses, there are multiple synchronization transitions with time delay, and the synchronization transition with coupling strength is dependent on the time delay lengths. For short delays we observe a single synchronization transition, whereas for long delays the neurons exhibit multiple synchronization transitions as the coupling strength is varied. These results show that gap junctions and chemical synapses have different impacts on the pattern formation and synchronization transitions of the scale-free MHH neuronal networks, and chemical synapses, compared to gap junctions, may play a dominant and more active function in the firing activity of the networks. These findings would be helpful for further understanding the roles of gap junctions and chemical synapses in the firing dynamics of neuronal networks.

  7. Linear Approach for Synchronous State Stability in Fully Connected PLL Networks

    Directory of Open Access Journals (Sweden)

    José R. C. Piqueira

    2008-01-01

    Full Text Available Synchronization is an essential feature for the use of digital systems in telecommunication networks, integrated circuits, and manufacturing automation. Formerly, master-slave (MS architectures, with precise master clock generators sending signals to phase-locked loops (PLLs working as slave oscillators, were considered the best solution. Nowadays, the development of wireless networks with dynamical connectivity and the increase of the size and the operation frequency of integrated circuits suggest that the distribution of clock signals could be more efficient if distributed solutions with fully connected oscillators are used. Here, fully connected networks with second-order PLLs as nodes are considered. In previous work, how the synchronous state frequency for this type of network depends on the node parameters and delays was studied and an expression for the long-term frequency was derived (Piqueira, 2006. Here, by taking the first term of the Taylor series expansion for the dynamical system description, it is shown that for a generic network with N nodes, the synchronous state is locally asymptotically stable.

  8. An Efficient Algorithm for Computing Attractors of Synchronous And Asynchronous Boolean Networks

    Science.gov (United States)

    Zheng, Desheng; Yang, Guowu; Li, Xiaoyu; Wang, Zhicai; Liu, Feng; He, Lei

    2013-01-01

    Biological networks, such as genetic regulatory networks, often contain positive and negative feedback loops that settle down to dynamically stable patterns. Identifying these patterns, the so-called attractors, can provide important insights for biologists to understand the molecular mechanisms underlying many coordinated cellular processes such as cellular division, differentiation, and homeostasis. Both synchronous and asynchronous Boolean networks have been used to simulate genetic regulatory networks and identify their attractors. The common methods of computing attractors are that start with a randomly selected initial state and finish with exhaustive search of the state space of a network. However, the time complexity of these methods grows exponentially with respect to the number and length of attractors. Here, we build two algorithms to achieve the computation of attractors in synchronous and asynchronous Boolean networks. For the synchronous scenario, combing with iterative methods and reduced order binary decision diagrams (ROBDD), we propose an improved algorithm to compute attractors. For another algorithm, the attractors of synchronous Boolean networks are utilized in asynchronous Boolean translation functions to derive attractors of asynchronous scenario. The proposed algorithms are implemented in a procedure called geneFAtt. Compared to existing tools such as genYsis, geneFAtt is significantly faster in computing attractors for empirical experimental systems. Availability The software package is available at https://sites.google.com/site/desheng619/download. PMID:23585840

  9. Robust synchronization of chaotic systems via feedback

    Energy Technology Data Exchange (ETDEWEB)

    Femat, Ricardo [IPICYT, San Luis Potosi (Mexico). Dept. de Matematicas Aplicadas; Solis-Perales, Gualberto [Universidad de Guadalajara, Centro Univ. de Ciencias Exactas e Ingenierias (Mexico). Div. de Electronica y Computacion

    2008-07-01

    This volume includes the results derived during last ten years about both suppression and synchronization of chaotic -continuous time- systems. Along this time, the concept was to study how the intrinsic properties of dynamical systems can be exploited to suppress and to synchronize the chaotic behaviour and what synchronization phenomena can be found under feedback interconnection. A compilation of these findings is described in this book. This book shows a perspective on synchronization of chaotic systems. (orig.)

  10. Synchronized High-Speed Vision Sensor Network for Expansion of Field of View

    Directory of Open Access Journals (Sweden)

    Akihito Noda

    2018-04-01

    Full Text Available We propose a 500-frames-per-second high-speed vision (HSV sensor network that acquires frames at a timing that is precisely synchronized across the network. Multiple vision sensor nodes, individually comprising a camera and a PC, are connected via Ethernet for data transmission and for clock synchronization. A network of synchronized HSV sensors provides a significantly expanded field-of-view compared with that of each individual HSV sensor. In the proposed system, the shutter of each camera is controlled based on the clock of the PC locally provided inside the node, and the shutters are globally synchronized using the Precision Time Protocol (PTP over the network. A theoretical analysis and experiment results indicate that the shutter trigger skew among the nodes is a few tens of microseconds at most, which is significantly smaller than the frame interval of 1000-fps-class high-speed cameras. Experimental results obtained with the proposed system comprising four nodes demonstrated the ability to capture the propagation of a small displacement along a large-scale structure.

  11. Characterizing and predicting the robustness of power-law networks

    International Nuclear Information System (INIS)

    LaRocca, Sarah; Guikema, Seth D.

    2015-01-01

    Power-law networks such as the Internet, terrorist cells, species relationships, and cellular metabolic interactions are susceptible to node failures, yet maintaining network connectivity is essential for network functionality. Disconnection of the network leads to fragmentation and, in some cases, collapse of the underlying system. However, the influences of the topology of networks on their ability to withstand node failures are poorly understood. Based on a study of the response of 2000 randomly-generated power-law networks to node failures, we find that networks with higher nodal degree and clustering coefficient, lower betweenness centrality, and lower variability in path length and clustering coefficient maintain their cohesion better during such events. We also find that network robustness, i.e., the ability to withstand node failures, can be accurately predicted a priori for power-law networks across many fields. These results provide a basis for designing new, more robust networks, improving the robustness of existing networks such as the Internet and cellular metabolic pathways, and efficiently degrading networks such as terrorist cells. - Highlights: • Examine relationship between network topology and robustness to failures. • Relationship is statistically significant for scale-free networks. • Use statistical models to estimate robustness to failures for real-world networks

  12. Chaotic synchronization of nearest-neighbor diffusive coupling Hindmarsh-Rose neural networks in noisy environments

    International Nuclear Information System (INIS)

    Fang Xiaoling; Yu Hongjie; Jiang Zonglai

    2009-01-01

    The chaotic synchronization of Hindmarsh-Rose neural networks linked by a nonlinear coupling function is discussed. The HR neural networks with nearest-neighbor diffusive coupling form are treated as numerical examples. By the construction of a special nonlinear-coupled term, the chaotic system is coupled symmetrically. For three and four neurons network, a certain region of coupling strength corresponding to full synchronization is given, and the effect of network structure and noise position are analyzed. For five and more neurons network, the full synchronization is very difficult to realize. All the results have been proved by the calculation of the maximum conditional Lyapunov exponent.

  13. A scoring mechanism for the rank aggregation of network robustness

    Science.gov (United States)

    Yazdani, Alireza; Dueñas-Osorio, Leonardo; Li, Qilin

    2013-10-01

    To date, a number of metrics have been proposed to quantify inherent robustness of network topology against failures. However, each single metric usually only offers a limited view of network vulnerability to different types of random failures and targeted attacks. When applied to certain network configurations, different metrics rank network topology robustness in different orders which is rather inconsistent, and no single metric fully characterizes network robustness against different modes of failure. To overcome such inconsistency, this work proposes a multi-metric approach as the basis of evaluating aggregate ranking of network topology robustness. This is based on simultaneous utilization of a minimal set of distinct robustness metrics that are standardized so to give way to a direct comparison of vulnerability across networks with different sizes and configurations, hence leading to an initial scoring of inherent topology robustness. Subsequently, based on the inputs of initial scoring a rank aggregation method is employed to allocate an overall ranking of robustness to each network topology. A discussion is presented in support of the presented multi-metric approach and its applications to more realistically assess and rank network topology robustness.

  14. Finite-time and fixed-time synchronization analysis of inertial memristive neural networks with time-varying delays.

    Science.gov (United States)

    Wei, Ruoyu; Cao, Jinde; Alsaedi, Ahmed

    2018-02-01

    This paper investigates the finite-time synchronization and fixed-time synchronization problems of inertial memristive neural networks with time-varying delays. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, several sufficient conditions are derived to ensure finite-time synchronization of inertial memristive neural networks. Then, for the purpose of making the setting time independent of initial condition, we consider the fixed-time synchronization. A novel criterion guaranteeing the fixed-time synchronization of inertial memristive neural networks is derived. Finally, three examples are provided to demonstrate the effectiveness of our main results.

  15. Finite time synchronization of memristor-based Cohen-Grossberg neural networks with mixed delays

    Science.gov (United States)

    2017-01-01

    Finite time synchronization, which means synchronization can be achieved in a settling time, is desirable in some practical applications. However, most of the published results on finite time synchronization don’t include delays or only include discrete delays. In view of the fact that distributed delays inevitably exist in neural networks, this paper aims to investigate the finite time synchronization of memristor-based Cohen-Grossberg neural networks (MCGNNs) with both discrete delay and distributed delay (mixed delays). By means of a simple feedback controller and novel finite time synchronization analysis methods, several new criteria are derived to ensure the finite time synchronization of MCGNNs with mixed delays. The obtained criteria are very concise and easy to verify. Numerical simulations are presented to demonstrate the effectiveness of our theoretical results. PMID:28931066

  16. Finite time synchronization of memristor-based Cohen-Grossberg neural networks with mixed delays.

    Science.gov (United States)

    Chen, Chuan; Li, Lixiang; Peng, Haipeng; Yang, Yixian

    2017-01-01

    Finite time synchronization, which means synchronization can be achieved in a settling time, is desirable in some practical applications. However, most of the published results on finite time synchronization don't include delays or only include discrete delays. In view of the fact that distributed delays inevitably exist in neural networks, this paper aims to investigate the finite time synchronization of memristor-based Cohen-Grossberg neural networks (MCGNNs) with both discrete delay and distributed delay (mixed delays). By means of a simple feedback controller and novel finite time synchronization analysis methods, several new criteria are derived to ensure the finite time synchronization of MCGNNs with mixed delays. The obtained criteria are very concise and easy to verify. Numerical simulations are presented to demonstrate the effectiveness of our theoretical results.

  17. Finite time synchronization of memristor-based Cohen-Grossberg neural networks with mixed delays.

    Directory of Open Access Journals (Sweden)

    Chuan Chen

    Full Text Available Finite time synchronization, which means synchronization can be achieved in a settling time, is desirable in some practical applications. However, most of the published results on finite time synchronization don't include delays or only include discrete delays. In view of the fact that distributed delays inevitably exist in neural networks, this paper aims to investigate the finite time synchronization of memristor-based Cohen-Grossberg neural networks (MCGNNs with both discrete delay and distributed delay (mixed delays. By means of a simple feedback controller and novel finite time synchronization analysis methods, several new criteria are derived to ensure the finite time synchronization of MCGNNs with mixed delays. The obtained criteria are very concise and easy to verify. Numerical simulations are presented to demonstrate the effectiveness of our theoretical results.

  18. Local and global synchronization in general complex dynamical networks with delay coupling

    International Nuclear Information System (INIS)

    Lu Jianquan; Ho, Daniel W.C.

    2008-01-01

    Local and global synchronization of complex dynamical networks are studied in this paper. Some simple yet generic criteria ensuring delay-independent and delay-dependent synchronization are derived in terms of linear matrix inequalities (LMIs), which can be verified easily via interior-point algorithm. The assumption that the coupling configuration matrix is symmetric and irreducible, which is frequently used in other literatures, is removed. A network with a fixed delay and a special coupling scheme is given as an example to illustrate the theoretical results and the effectiveness of the proposed synchronization scheme

  19. Coevolution of Synchronization and Cooperation in Costly Networked Interactions

    Science.gov (United States)

    Antonioni, Alberto; Cardillo, Alessio

    2017-06-01

    Despite the large number of studies on synchronization, the hypothesis that interactions bear a cost for involved individuals has seldom been considered. The introduction of costly interactions leads, instead, to the formulation of a dichotomous scenario in which an individual may decide to cooperate and pay the cost in order to get synchronized with the rest of the population. Alternatively, the same individual can decide to free ride, without incurring any cost, waiting for others to get synchronized to his or her state. Thus, the emergence of synchronization may be seen as the byproduct of an evolutionary game in which individuals decide their behavior according to the benefit-to-cost ratio they accrued in the past. We study the onset of cooperation and synchronization in networked populations of Kuramoto oscillators and report how topology is essential in order for cooperation to thrive. We also display how different classes of topology foster synchronization differently both at microscopic and macroscopic levels.

  20. Suppression of anomalous synchronization and nonstationary behavior of neural network under small-world topology

    Science.gov (United States)

    Boaretto, B. R. R.; Budzinski, R. C.; Prado, T. L.; Kurths, J.; Lopes, S. R.

    2018-05-01

    It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the anomalous synchronization and also to diminish the nonstationary behavior occurring in weakly coupled neural network under small-world topology. We consider a network of 2000 thermally sensitive identical neurons, based on the model of Hodgkin-Huxley in a small-world topology, with the probability of adding non local connection equal to p = 0 . 001. Based on experimental protocols to suppress anomalous synchronization, as well as nonstationary behavior of the neural network dynamics, we make use of (i) external stimulus (pulsed current); (ii) biologic parameters changing (neuron membrane conductance changes); and (iii) body temperature changes. Quantification analysis to evaluate phase synchronization makes use of the Kuramoto's order parameter, while recurrence quantification analysis, particularly the determinism, computed over the easily accessible mean field of network, the local field potential (LFP), is used to evaluate nonstationary states. We show that the methods proposed can control the anomalous synchronization and nonstationarity occurring for weak coupling parameter without any effect on the individual neuron dynamics, neither in the expected asymptotic synchronized states occurring for large values of the coupling parameter.

  1. Are networks with more edges easier to synchronize, or not?

    International Nuclear Information System (INIS)

    Zhi-Sheng, Duan; Chao, Liu; Guan-Rong, Chen; Wen-Xu, Wang

    2009-01-01

    In this paper, the relationship between network synchronizability and the edge-addition of its associated graph is investigated. First, it is shown that adding one edge to a cycle definitely decreases the network synchronizability. Then, since sometimes the synchronizability can be enhanced by changing the network structure, the question of whether the networks with more edges are easier to synchronize is addressed. Based on a subgraph and complementary graph method, it is shown by examples that the answer is negative even if the network structure is arbitrarily optimized. This reveals that generally there are redundant edges in a network, which not only make no contributions to synchronization but actually may reduce the synchronizability. Moreover, a simple example shows that the node betweenness centrality is not always a good indicator for the network synchronizability. Finally, some more examples are presented to illustrate how the network synchronizability varies following the addition of edges, where all the examples show that the network synchronizability globally increases but locally fluctuates as the number of added edges increases. (general)

  2. Closeness-Centrality-Based Synchronization Criteria for Complex Dynamical Networks With Interval Time-Varying Coupling Delays.

    Science.gov (United States)

    Park, Myeongjin; Lee, Seung-Hoon; Kwon, Oh-Min; Seuret, Alexandre

    2017-09-06

    This paper investigates synchronization in complex dynamical networks (CDNs) with interval time-varying delays. The CDNs are representative of systems composed of a large number of interconnected dynamical units, and for the purpose of the mathematical analysis, the leading work is to model them as graphs whose nodes represent the dynamical units. At this time, we take note of the importance of each node in networks. One way, in this paper, is that the closeness-centrality mentioned in the field of social science is grafted onto the CDNs. By constructing a suitable Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient and closeness-centrality-based conditions for synchronization stability of the networks are established in terms of linear matrix inequalities. Ultimately, the use of the closeness-centrality can be weighted with regard to not only the interconnection relation among the nodes, which was utilized in the existing works but also more information about nodes. Here, the centrality will be added as the concerned information. Moreover, to avoid the computational burden causing the nonconvex term including the square of the time-varying delay, how to deal with it is applied by estimating it to the convex term including time-varying delay. Finally, two illustrative examples are given to show the advantage of the closeness-centrality in point of the robustness on time-delay.

  3. Synchronized stability in a reaction–diffusion neural network model

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Ling; Zhao, Hongyong, E-mail: hongyongz@126.com

    2014-11-14

    The reaction–diffusion neural network consisting of a pair of identical tri-neuron loops is considered. We present detailed discussions about the synchronized stability and Hopf bifurcation, deducing the non-trivial role that delay plays in different locations. The corresponding numerical simulations are used to illustrate the effectiveness of the obtained results. In addition, the numerical results about the effects of diffusion reveal that diffusion may speed up the tendency to synchronization and induce the synchronized equilibrium point to be stable. Furthermore, if the parameters are located in appropriate regions, multiple unstability and bistability or unstability and bistability may coexist. - Highlights: • Point to non-trivial role that τ plays in different positions. • Diffusion speeds up the tendency to synchronization. • Diffusion induces the synchronized equilibrium point to be stable. • The coexistence of multiple unstability and bistability or unstability and bistability.

  4. Synchronized stability in a reaction–diffusion neural network model

    International Nuclear Information System (INIS)

    Wang, Ling; Zhao, Hongyong

    2014-01-01

    The reaction–diffusion neural network consisting of a pair of identical tri-neuron loops is considered. We present detailed discussions about the synchronized stability and Hopf bifurcation, deducing the non-trivial role that delay plays in different locations. The corresponding numerical simulations are used to illustrate the effectiveness of the obtained results. In addition, the numerical results about the effects of diffusion reveal that diffusion may speed up the tendency to synchronization and induce the synchronized equilibrium point to be stable. Furthermore, if the parameters are located in appropriate regions, multiple unstability and bistability or unstability and bistability may coexist. - Highlights: • Point to non-trivial role that τ plays in different positions. • Diffusion speeds up the tendency to synchronization. • Diffusion induces the synchronized equilibrium point to be stable. • The coexistence of multiple unstability and bistability or unstability and bistability

  5. Unified synchronization criteria in an array of coupled neural networks with hybrid impulses.

    Science.gov (United States)

    Wang, Nan; Li, Xuechen; Lu, Jianquan; Alsaadi, Fuad E

    2018-05-01

    This paper investigates the problem of globally exponential synchronization of coupled neural networks with hybrid impulses. Two new concepts on average impulsive interval and average impulsive gain are proposed to deal with the difficulties coming from hybrid impulses. By employing the Lyapunov method combined with some mathematical analysis, some efficient unified criteria are obtained to guarantee the globally exponential synchronization of impulsive networks. Our method and criteria are proved to be effective for impulsively coupled neural networks simultaneously with synchronizing impulses and desynchronizing impulses, and we do not need to discuss these two kinds of impulses separately. Moreover, by using our average impulsive interval method, we can obtain an interesting and valuable result for the case of average impulsive interval T a =∞. For some sparse impulsive sequences with T a =∞, the impulses can happen for infinite number of times, but they do not have essential influence on the synchronization property of networks. Finally, numerical examples including scale-free networks are exploited to illustrate our theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. A plasma switch synchronous closing operations in high-voltage networks

    International Nuclear Information System (INIS)

    Mourente, P.

    1984-01-01

    Overvoltages and overcurrent arising in energizing or in fast reclosing operations are a concerning problem in high-voltage networks. Reduction of overvoltages and overcurrents is possible using the synchronous closing technique. Some attempts have been done to perform the synchronous closing with conventional circuit-breakers. But since the requirements to synchronous closing and to current interruption are very contradictory this technique is not yet a common practice. Three simple cases may be used as examples to show the benefits of synchronous closing; energizaton of grounded star capacitor bank; back-to-back switching of large capacitor banks; and fast reclosing on transmission lines

  7. Time synchronization for an Ethernet-based real-time token network

    NARCIS (Netherlands)

    Hanssen, F.T.Y.; van den Boom, Joost; Jansen, P.G.; Scholten, Johan

    We present a distributed clock synchronization algorithm. It performs clock synchronization on an Ethernet-based real-time token local area network, without the use of an external clock source. It is used to enable the token schedulers in each node to agree upon a common time. Its intended use is in

  8. Chaos Control and Synchronization of Cellular Neural Network with Delays Based on OPNCL Control

    International Nuclear Information System (INIS)

    Qian, Tang; Xing-Yuan, Wang

    2010-01-01

    The problem of chaos control and complete synchronization of cellular neural network with delays is studied. Based on the open plus nonlinear closed loop (OPNCL) method, the control scheme and synchronization scheme are designed. Both the schemes can achieve the chaos control and complete synchronization of chaotic neural network respectively, and their validity is further verified by numerical simulation experiments. (general)

  9. Robustness and modular structure in networks

    DEFF Research Database (Denmark)

    Bagrow, James P.; Lehmann, Sune; Ahn, Yong-Yeol

    2015-01-01

    -12]. Many complex systems, from power grids and the Internet to the brain and society [13-15], can be modeled using modular networks comprised of small, densely connected groups of nodes [16, 17]. These modules often overlap, with network elements belonging to multiple modules [18, 19]. Yet existing work...... on robustness has not considered the role of overlapping, modular structure. Here we study the robustness of these systems to the failure of elements. We show analytically and empirically that it is possible for the modules themselves to become uncoupled or non-overlapping well before the network disintegrates....... If overlapping modular organization plays a role in overall functionality, networks may be far more vulnerable than predicted by conventional percolation theory....

  10. Effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks

    Science.gov (United States)

    Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen

    2017-05-01

    In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay pdelay, whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.

  11. Benchmarking and monitoring framework for interconnected file synchronization and sharing services

    DEFF Research Database (Denmark)

    Mrówczyński, Piotr; Mościcki, Jakub T.; Lamanna, Massimo

    2018-01-01

    computing and storage infrastructure in the research labs. In this work we present a benchmarking and monitoring framework for file synchronization and sharing services. It allows service providers to monitor the operational status of their services, understand the service behavior under different load...... types and with different network locations of the synchronization clients. The framework is designed as a monitoring and benchmarking tool to provide performance and robustness metrics for interconnected file synchronization and sharing services such as Open Cloud Mesh....

  12. Synchronization of Reaction-Diffusion Neural Networks With Dirichlet Boundary Conditions and Infinite Delays.

    Science.gov (United States)

    Sheng, Yin; Zhang, Hao; Zeng, Zhigang

    2017-10-01

    This paper is concerned with synchronization for a class of reaction-diffusion neural networks with Dirichlet boundary conditions and infinite discrete time-varying delays. By utilizing theories of partial differential equations, Green's formula, inequality techniques, and the concept of comparison, algebraic criteria are presented to guarantee master-slave synchronization of the underlying reaction-diffusion neural networks via a designed controller. Additionally, sufficient conditions on exponential synchronization of reaction-diffusion neural networks with finite time-varying delays are established. The proposed criteria herein enhance and generalize some published ones. Three numerical examples are presented to substantiate the validity and merits of the obtained theoretical results.

  13. Backoff-stage synchronization in three-hop string-topology wireless networks with hidden nodes

    Science.gov (United States)

    Sanada, Kosuke; Sekiya, Hiroo; Komuro, Nobuyoshi; Sakata, Shiro

    In IEEE 802.11 wireless multi-hop networks, each node works individually and their individual operations generate entire network dynamics. It is important to clarify the network dynamics in wireless multi-hop networks for designing and constructing multi-hop communication networks. This paper presents the network-dynamics investigations for three-hop string-topology wireless network in detail. From the investigations, a “backoff-stage synchronization” phenomenon, which is mutuality between hidden nodes, is found. The mechanism of the backoff-stage synchronization is expressed and the sufficient conditions for the synchronization occurrence are given. This phenomenon gives some impacts on the IEEE 802.11 multi-hop-network communications.

  14. Periodic synchronization control of discontinuous delayed networks by using extended Filippov-framework.

    Science.gov (United States)

    Cai, Zuowei; Huang, Lihong; Guo, Zhenyuan; Zhang, Lingling; Wan, Xuting

    2015-08-01

    This paper is concerned with the periodic synchronization problem for a general class of delayed neural networks (DNNs) with discontinuous neuron activation. One of the purposes is to analyze the problem of periodic orbits. To do so, we introduce new tools including inequality techniques and Kakutani's fixed point theorem of set-valued maps to derive the existence of periodic solution. Another purpose is to design a switching state-feedback control for realizing global exponential synchronization of the drive-response network system with periodic coefficients. Unlike the previous works on periodic synchronization of neural network, both the neuron activations and controllers in this paper are allowed to be discontinuous. Moreover, owing to the occurrence of delays in neuron signal, the neural network model is described by the functional differential equation. So we introduce extended Filippov-framework to deal with the basic issues of solutions for discontinuous DNNs. Finally, two examples and simulation experiments are given to illustrate the proposed method and main results which have an important instructional significance in the design of periodic synchronized DNNs circuits involving discontinuous or switching factors. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Energy-efficient pulse-coupled synchronization strategy design for wireless sensor networks through reduced idle listening

    Science.gov (United States)

    Wang, Yongqiang; Núñez, Felipe; Doyle, Francis J.

    2013-01-01

    Synchronization is crucial to wireless sensor networks due to their decentralized structure. We propose an energy-efficient pulse-coupled synchronization strategy to achieve this goal. The basic idea is to reduce idle listening by intentionally introducing a large refractory period in the sensors’ cooperation. The large refractory period greatly reduces idle listening in each oscillation period, and is analytically proven to have no influence on the time to synchronization. Hence, it significantly reduces the total energy consumption in a synchronization process. A topology control approach tailored for pulse-coupled synchronization is given to guarantee a k-edge strongly connected interaction topology, which is tolerant to communication-link failures. The topology control approach is totally decentralized and needs no information exchange among sensors, and it is applicable to dynamic network topologies as well. This facilitates a completely decentralized implementation of the synchronization strategy. The strategy is applicable to mobile sensor networks, too. QualNet case studies confirm the effectiveness of the synchronization strategy. PMID:24307831

  16. Robust network topologies for generating switch-like cellular responses.

    Directory of Open Access Journals (Sweden)

    Najaf A Shah

    2011-06-01

    Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

  17. Approximability of Robust Network Design

    NARCIS (Netherlands)

    Olver, N.K.; Shepherd, F.B.

    2014-01-01

    We consider robust (undirected) network design (RND) problems where the set of feasible demands may be given by an arbitrary convex body. This model, introduced by Ben-Ameur and Kerivin [Ben-Ameur W, Kerivin H (2003) New economical virtual private networks. Comm. ACM 46(6):69-73], generalizes the

  18. Robust haptic large distance telemanipulation for ITER

    International Nuclear Information System (INIS)

    Heck, D.J.F.; Heemskerk, C.J.M.; Koning, J.F.; Abbasi, A.; Nijmeijer, H.

    2013-01-01

    Highlights: • ITER remote handling maintenance can be controlled safely over a large distance. • Bilateral teleoperation experiments were performed in a local network. • Wave variables make the controller robust against constant communication delays. • Master and slave position synchronization guaranteed by proportional action. -- Abstract: During shutdowns, maintenance crews are expected to work in 24/6 shifts to perform critical remote handling maintenance tasks on the ITER system. In this article, we investigate the possibility to safely perform these haptic maintenance tasks remotely from control stations located anywhere around the world. To guarantee stability in time delayed bilateral teleoperation, the symmetric position tracking controller using wave variables is selected. This algorithm guarantees robustness against communication delays, can eliminate wave reflections and provide position synchronization of the master and slave devices. Experiments have been conducted under realistic local network bandwidth, latency and jitter constraints. They show sufficient transparency even for substantial communication delays

  19. Robust haptic large distance telemanipulation for ITER

    Energy Technology Data Exchange (ETDEWEB)

    Heck, D.J.F., E-mail: d.j.f.heck@tue.nl [Eindhoven University of Technology, Department of Mechanical Engineering, Eindhoven (Netherlands); Heemskerk, C.J.M.; Koning, J.F. [Heemskerk Innovative Technologies, Sassenheim (Netherlands); Abbasi, A.; Nijmeijer, H. [Eindhoven University of Technology, Department of Mechanical Engineering, Eindhoven (Netherlands)

    2013-10-15

    Highlights: • ITER remote handling maintenance can be controlled safely over a large distance. • Bilateral teleoperation experiments were performed in a local network. • Wave variables make the controller robust against constant communication delays. • Master and slave position synchronization guaranteed by proportional action. -- Abstract: During shutdowns, maintenance crews are expected to work in 24/6 shifts to perform critical remote handling maintenance tasks on the ITER system. In this article, we investigate the possibility to safely perform these haptic maintenance tasks remotely from control stations located anywhere around the world. To guarantee stability in time delayed bilateral teleoperation, the symmetric position tracking controller using wave variables is selected. This algorithm guarantees robustness against communication delays, can eliminate wave reflections and provide position synchronization of the master and slave devices. Experiments have been conducted under realistic local network bandwidth, latency and jitter constraints. They show sufficient transparency even for substantial communication delays.

  20. Pinning control of complex networked systems synchronization, consensus and flocking of networked systems via pinning

    CERN Document Server

    Su, Housheng

    2013-01-01

    Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Contro...

  1. A proportional integral estimator-based clock synchronization protocol for wireless sensor networks.

    Science.gov (United States)

    Yang, Wenlun; Fu, Minyue

    2017-11-01

    Clock synchronization is an issue of vital importance in applications of WSNs. This paper proposes a proportional integral estimator-based protocol (EBP) to achieve clock synchronization for wireless sensor networks. As each local clock skew gradually drifts, synchronization accuracy will decline over time. Compared with existing consensus-based approaches, the proposed synchronization protocol improves synchronization accuracy under time-varying clock skews. Moreover, by restricting synchronization error of clock skew into a relative small quantity, it could reduce periodic re-synchronization frequencies. At last, a pseudo-synchronous implementation for skew compensation is introduced as synchronous protocol is unrealistic in practice. Numerical simulations are shown to illustrate the performance of the proposed protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Experimental realization of synchronization in complex networks with Chua's circuits like nodes

    International Nuclear Information System (INIS)

    Posadas-Castillo, C.; Cruz-Hernandez, C.; Lopez-Gutierrez, R.M.

    2009-01-01

    In this paper, an experimental study on practical realization of synchronization in globally coupled networks with Chua's circuits like nodes is presented. Synchronization of coupled multiple Chua's circuits is achieved by appealing to results from complex systems theory. In particular, we design and implement electronically complex dynamical networks composed by three coupled Chua's circuits, considering two scenarios: (i) without master node, and (ii) with (periodic and chaotic) master node. The interactions in the networks are defined by coupling the first state of each Chua's circuit.

  3. Robustness of networks against propagating attacks under vaccination strategies

    International Nuclear Information System (INIS)

    Hasegawa, Takehisa; Masuda, Naoki

    2011-01-01

    We study the effect of vaccination on the robustness of networks against propagating attacks that obey the susceptible–infected–removed model. By extending the generating function formalism developed by Newman (2005 Phys. Rev. Lett. 95 108701), we analytically determine the robustness of networks that depends on the vaccination parameters. We consider the random defense where nodes are vaccinated randomly and the degree-based defense where hubs are preferentially vaccinated. We show that, when vaccines are inefficient, the random graph is more robust against propagating attacks than the scale-free network. When vaccines are relatively efficient, the scale-free network with the degree-based defense is more robust than the random graph with the random defense and the scale-free network with the random defense

  4. Interplay of delay and multiplexing: Impact on cluster synchronization

    Science.gov (United States)

    Singh, Aradhana; Jalan, Sarika; Boccaletti, Stefano

    2017-04-01

    Communication delays and multiplexing are ubiquitous features of real-world network systems. We here introduce a simple model where these two features are simultaneously present and report the rich phenomenology which is actually due to their interplay on cluster synchronization. A delay in one layer has non trivial impacts on the collective dynamics of the other layers, enhancing or suppressing synchronization. At the same time, multiplexing may also enhance cluster synchronization of delayed layers. We elucidate several nontrivial (and anti-intuitive) scenarios, which are of interest and potential application in various real-world systems, where the introduction of a delay may render synchronization of a layer robust against changes in the properties of the other layers.

  5. Clock Synchronization for Multihop Wireless Sensor Networks

    Science.gov (United States)

    Solis Robles, Roberto

    2009-01-01

    In wireless sensor networks, more so generally than in other types of distributed systems, clock synchronization is crucial since by having this service available, several applications such as media access protocols, object tracking, or data fusion, would improve their performance. In this dissertation, we propose a set of algorithms to achieve…

  6. A precise time synchronization method for 5G based on radio-over-fiber network with SDN controller

    Science.gov (United States)

    He, Linkuan; Wei, Baoguo; Yang, Hui; Yu, Ao; Wang, Zhengyong; Zhang, Jie

    2018-02-01

    There is an increasing demand on accurate time synchronization with the growing bandwidth of network service for 5G. In 5G network, it's necessary for base station to achieve accurate time synchronization to guarantee the quality of communication. In order to keep accuracy time for 5G network, we propose a time synchronization system for satellite ground station based on radio-over-fiber network (RoFN) with software defined optical network (SDON) controller. The advantage of this method is to improve the accuracy of time synchronization of ground station. The IEEE 1588 time synchronization protocol can solve the problems of high cost and lack of precision. However, in the process of time synchronization, distortion exists during the transmission of digital time signal. RoF uses analog optical transmission links and therefore analog transmission can be implemented among ground stations instead of digital transmission, which means distortion and bandwidth waste in the process of digital synchronization can be avoided. Additionally, the thought of SDN, software defined network, can optimize RoFN with centralized control and simplifying base station. Related simulation had been carried out to prove its superiority.

  7. Complex network synchronization of chaotic systems with delay coupling

    International Nuclear Information System (INIS)

    Theesar, S. Jeeva Sathya; Ratnavelu, K.

    2014-01-01

    The study of complex networks enables us to understand the collective behavior of the interconnected elements and provides vast real time applications from biology to laser dynamics. In this paper, synchronization of complex network of chaotic systems has been studied. Every identical node in the complex network is assumed to be in Lur’e system form. In particular, delayed coupling has been assumed along with identical sector bounded nonlinear systems which are interconnected over network topology

  8. Time concurrency/phase-time synchronization in digital communications networks

    Science.gov (United States)

    Kihara, Masami; Imaoka, Atsushi

    1990-01-01

    Digital communications networks have the intrinsic capability of time synchronization which makes it possible for networks to supply time signals to some applications and services. A practical estimation method for the time concurrency on terrestrial networks is presented. By using this method, time concurrency capability of the Nippon Telegraph and Telephone Corporation (NTT) digital communications network is estimated to be better than 300 ns rms at an advanced level, and 20 ns rms at final level.

  9. Event-triggered synchronization for reaction-diffusion complex networks via random sampling

    Science.gov (United States)

    Dong, Tao; Wang, Aijuan; Zhu, Huiyun; Liao, Xiaofeng

    2018-04-01

    In this paper, the synchronization problem of the reaction-diffusion complex networks (RDCNs) with Dirichlet boundary conditions is considered, where the data is sampled randomly. An event-triggered controller based on the sampled data is proposed, which can reduce the number of controller and the communication load. Under this strategy, the synchronization problem of the diffusion complex network is equivalently converted to the stability of a of reaction-diffusion complex dynamical systems with time delay. By using the matrix inequality technique and Lyapunov method, the synchronization conditions of the RDCNs are derived, which are dependent on the diffusion term. Moreover, it is found the proposed control strategy can get rid of the Zeno behavior naturally. Finally, a numerical example is given to verify the obtained results.

  10. Social and Virtual Networks: Evaluating Synchronous Online Interviewing Using Instant Messenger

    Science.gov (United States)

    Hinchcliffe, Vanessa; Gavin, Helen

    2009-01-01

    This paper describes an evaluation of the quality and utility of synchronous online interviewing for data collection in social network research. Synchronous online interviews facilitated by Instant Messenger as the communication medium, were undertaken with ten final year university students. Quantitative and qualitative content analysis of…

  11. Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance.

    Science.gov (United States)

    Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

    2017-03-14

    Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.

  12. Tension and robustness in multitasking cellular networks.

    Directory of Open Access Journals (Sweden)

    Jeffrey V Wong

    Full Text Available Cellular networks multitask by exhibiting distinct, context-dependent dynamics. However, network states (parameters that generate a particular dynamic are often sub-optimal for others, defining a source of "tension" between them. Though multitasking is pervasive, it is not clear where tension arises, what consequences it has, and how it is resolved. We developed a generic computational framework to examine the source and consequences of tension between pairs of dynamics exhibited by the well-studied RB-E2F switch regulating cell cycle entry. We found that tension arose from task-dependent shifts in parameters associated with network modules. Although parameter sets common to distinct dynamics did exist, tension reduced both their accessibility and resilience to perturbation, indicating a trade-off between "one-size-fits-all" solutions and robustness. With high tension, robustness can be preserved by dynamic shifting of modules, enabling the network to toggle between tasks, and by increasing network complexity, in this case by gene duplication. We propose that tension is a general constraint on the architecture and operation of multitasking biological networks. To this end, our work provides a framework to quantify the extent of tension between any network dynamics and how it affects network robustness. Such analysis would suggest new ways to interfere with network elements to elucidate the design principles of cellular networks.

  13. Dynamic synchronization of a time-evolving optical network of chaotic oscillators.

    Science.gov (United States)

    Cohen, Adam B; Ravoori, Bhargava; Sorrentino, Francesco; Murphy, Thomas E; Ott, Edward; Roy, Rajarshi

    2010-12-01

    We present and experimentally demonstrate a technique for achieving and maintaining a global state of identical synchrony of an arbitrary network of chaotic oscillators even when the coupling strengths are unknown and time-varying. At each node an adaptive synchronization algorithm dynamically estimates the current strength of the net coupling signal to that node. We experimentally demonstrate this scheme in a network of three bidirectionally coupled chaotic optoelectronic feedback loops and we present numerical simulations showing its application in larger networks. The stability of the synchronous state for arbitrary coupling topologies is analyzed via a master stability function approach. © 2010 American Institute of Physics.

  14. Synchronization and symmetry-breaking bifurcations in constructive networks of coupled chaotic oscillators

    International Nuclear Information System (INIS)

    Jiang Yu; Lozada-Cassou, M.; Vinet, A.

    2003-01-01

    The spatiotemporal dynamics of networks based on a ring of coupled oscillators with regular shortcuts beyond the nearest-neighbor couplings is studied by using master stability equations and numerical simulations. The generic criterion for dynamic synchronization has been extended to arbitrary network topologies with zero row-sum. The symmetry-breaking oscillation patterns that resulted from the Hopf bifurcation from synchronous states are analyzed by the symmetry group theory

  15. Projective synchronization of a complex network with different fractional order chaos nodes

    International Nuclear Information System (INIS)

    Wang Ming-Jun; Wang Xing-Yuan; Niu Yu-Jun

    2011-01-01

    Based on the stability theory of the linear fractional order system, projective synchronization of a complex network is studied in the paper, and the coupling functions of the connected nodes are identified. With this method, the projective synchronization of the network with different fractional order chaos nodes can be achieved, besides, the number of the nodes does not affect the stability of the whole network. In the numerical simulations, the chaotic fractional order Lü system, Liu system and Coullet system are chosen as examples to show the effectiveness of the scheme. (general)

  16. SYNCHRONIZATION OF HETEROGENEOUS OSCILLATORS UNDER NETWORK MODIFICATIONS: PERTURBATION AND OPTIMIZATION OF THE SYNCHRONY ALIGNMENT FUNCTION

    Science.gov (United States)

    Taylor, Dane; Skardal, Per Sebastian; Sun, Jie

    2016-01-01

    Synchronization is central to many complex systems in engineering physics (e.g., the power-grid, Josephson junction circuits, and electro-chemical oscillators) and biology (e.g., neuronal, circadian, and cardiac rhythms). Despite these widespread applications—for which proper functionality depends sensitively on the extent of synchronization—there remains a lack of understanding for how systems can best evolve and adapt to enhance or inhibit synchronization. We study how network modifications affect the synchronization properties of network-coupled dynamical systems that have heterogeneous node dynamics (e.g., phase oscillators with non-identical frequencies), which is often the case for real-world systems. Our approach relies on a synchrony alignment function (SAF) that quantifies the interplay between heterogeneity of the network and of the oscillators and provides an objective measure for a system’s ability to synchronize. We conduct a spectral perturbation analysis of the SAF for structural network modifications including the addition and removal of edges, which subsequently ranks the edges according to their importance to synchronization. Based on this analysis, we develop gradient-descent algorithms to efficiently solve optimization problems that aim to maximize phase synchronization via network modifications. We support these and other results with numerical experiments. PMID:27872501

  17. Master-slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control.

    Science.gov (United States)

    Li, Xiaofan; Fang, Jian-An; Li, Huiyuan

    2017-09-01

    This paper investigates master-slave exponential synchronization for a class of complex-valued memristor-based neural networks with time-varying delays via discontinuous impulsive control. Firstly, the master and slave complex-valued memristor-based neural networks with time-varying delays are translated to two real-valued memristor-based neural networks. Secondly, an impulsive control law is constructed and utilized to guarantee master-slave exponential synchronization of the neural networks. Thirdly, the master-slave synchronization problems are transformed into the stability problems of the master-slave error system. By employing linear matrix inequality (LMI) technique and constructing an appropriate Lyapunov-Krasovskii functional, some sufficient synchronization criteria are derived. Finally, a numerical simulation is provided to illustrate the effectiveness of the obtained theoretical results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Critical cooperation range to improve spatial network robustness.

    Directory of Open Access Journals (Sweden)

    Vitor H P Louzada

    Full Text Available A robust worldwide air-transportation network (WAN is one that minimizes the number of stranded passengers under a sequence of airport closures. Building on top of this realistic example, here we address how spatial network robustness can profit from cooperation between local actors. We swap a series of links within a certain distance, a cooperation range, while following typical constraints of spatially embedded networks. We find that the network robustness is only improved above a critical cooperation range. Such improvement can be described in the framework of a continuum transition, where the critical exponents depend on the spatial correlation of connected nodes. For the WAN we show that, except for Australia, all continental networks fall into the same universality class. Practical implications of this result are also discussed.

  19. Adaptive Asymptotical Synchronization for Stochastic Complex Networks with Time-Delay and Markovian Switching

    Directory of Open Access Journals (Sweden)

    Xueling Jiang

    2014-01-01

    Full Text Available The problem of adaptive asymptotical synchronization is discussed for the stochastic complex dynamical networks with time-delay and Markovian switching. By applying the stochastic analysis approach and the M-matrix method for stochastic complex networks, several sufficient conditions to ensure adaptive asymptotical synchronization for stochastic complex networks are derived. Through the adaptive feedback control techniques, some suitable parameters update laws are obtained. Simulation result is provided to substantiate the effectiveness and characteristics of the proposed approach.

  20. Complete synchronization of the global coupled dynamical network induced by Poisson noises.

    Science.gov (United States)

    Guo, Qing; Wan, Fangyi

    2017-01-01

    The different Poisson noise-induced complete synchronization of the global coupled dynamical network is investigated. Based on the stability theory of stochastic differential equations driven by Poisson process, we can prove that Poisson noises can induce synchronization and sufficient conditions are established to achieve complete synchronization with probability 1. Furthermore, numerical examples are provided to show the agreement between theoretical and numerical analysis.

  1. Stability analysis and synchronization in discrete-time complex networks with delayed coupling

    Science.gov (United States)

    Cheng, Ranran; Peng, Mingshu; Yu, Weibin; Sun, Bo; Yu, Jinchen

    2013-12-01

    A new network of coupled maps is proposed in which the connections between units involve no delays but the intra-neural communication does, whereas in the work of Atay et al. [Phys. Rev. Lett. 92, 144101 (2004)], the focus is on information processing delayed by the inter-neural communication. We show that the synchronization of the network depends on not only the intrinsic dynamical features and inter-connection topology (characterized by the spectrum of the graph Laplacian) but also the delays and the coupling strength. There are two main findings: (i) the more neighbours, the easier to be synchronized; (ii) odd delays are easier to be synchronized than even ones. In addition, compared with those discussed by Atay et al. [Phys. Rev. Lett. 92, 144101 (2004)], our model has a better synchronizability for regular networks and small-world variants.

  2. Robust Learning of High-dimensional Biological Networks with Bayesian Networks

    Science.gov (United States)

    Nägele, Andreas; Dejori, Mathäus; Stetter, Martin

    Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.

  3. Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

    Science.gov (United States)

    Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Management of synchronized network activity by highly active neurons

    International Nuclear Information System (INIS)

    Shein, Mark; Raichman, Nadav; Ben-Jacob, Eshel; Volman, Vladislav; Hanein, Yael

    2008-01-01

    Increasing evidence supports the idea that spontaneous brain activity may have an important functional role. Cultured neuronal networks provide a suitable model system to search for the mechanisms by which neuronal spontaneous activity is maintained and regulated. This activity is marked by synchronized bursting events (SBEs)—short time windows (hundreds of milliseconds) of rapid neuronal firing separated by long quiescent periods (seconds). However, there exists a special subset of rapidly firing neurons whose activity also persists between SBEs. It has been proposed that these highly active (HA) neurons play an important role in the management (i.e. establishment, maintenance and regulation) of the synchronized network activity. Here, we studied the dynamical properties and the functional role of HA neurons in homogeneous and engineered networks, during early network development, upon recovery from chemical inhibition and in response to electrical stimulations. We found that their sequences of inter-spike intervals (ISI) exhibit long time correlations and a unimodal distribution. During the network's development and under intense inhibition, the observed activity follows a transition period during which mostly HA neurons are active. Studying networks with engineered geometry, we found that HA neurons are precursors (the first to fire) of the spontaneous SBEs and are more responsive to electrical stimulations

  5. The networks scale and coupling parameter in synchronization of neural networks with diluted synapses

    International Nuclear Information System (INIS)

    Li Yanlong; Ma Jun; Chen Yuhong; Xu Wenke; Wang Yinghai

    2008-01-01

    In this paper the influence of the networks scale on the coupling parameter in the synchronization of neural networks with diluted synapses is investigated. Using numerical simulations, an exponential decay form is observed in the extreme case of global coupling among networks and full connection in each network; the larger linked degree becomes, the larger critical coupling intensity becomes; and the oscillation phenomena in the relationship of critical coupling intensity and the number of neural networks layers in the case of small-scale networks are found

  6. Robust Optimization of Fourth Party Logistics Network Design under Disruptions

    Directory of Open Access Journals (Sweden)

    Jia Li

    2015-01-01

    Full Text Available The Fourth Party Logistics (4PL network faces disruptions of various sorts under the dynamic and complex environment. In order to explore the robustness of the network, the 4PL network design with consideration of random disruptions is studied. The purpose of the research is to construct a 4PL network that can provide satisfactory service to customers at a lower cost when disruptions strike. Based on the definition of β-robustness, a robust optimization model of 4PL network design under disruptions is established. Based on the NP-hard characteristic of the problem, the artificial fish swarm algorithm (AFSA and the genetic algorithm (GA are developed. The effectiveness of the algorithms is tested and compared by simulation examples. By comparing the optimal solutions of the 4PL network for different robustness level, it is indicated that the robust optimization model can evade the market risks effectively and save the cost in the maximum limit when it is applied to 4PL network design.

  7. Synchronization between Different Networks with Time-Varying Delay and Its Application in Bilayer Coupled Public Traffic Network

    Directory of Open Access Journals (Sweden)

    Wenju Du

    2016-01-01

    Full Text Available In order to study the dynamic characteristics of urban public traffic network, this paper establishes the conventional bus traffic network and the urban rail traffic network based on the space R modeling method. Then regarding these two networks as the subnetwork, the paper presents a new bilayer coupled public traffic network through the transfer relationship between subway and bus, and this model well reflects the connection between the passengers and bus operating vehicles. Based on the synchronization theory of coupling network with time-varying delay and taking “Lorenz system” as the network node, the paper studies the synchronization of bilayer coupled public traffic network. Finally, numerical results are given to show the impact of public traffic dispatching, delayed departure, the number of public bus stops between bus lines, and the number of transfer stations between two traffic modes on the bilayer coupled public traffic network balance through Matlab simulation.

  8. Optimization of robustness of interdependent network controllability by redundant design.

    Directory of Open Access Journals (Sweden)

    Zenghu Zhang

    Full Text Available Controllability of complex networks has been a hot topic in recent years. Real networks regarded as interdependent networks are always coupled together by multiple networks. The cascading process of interdependent networks including interdependent failure and overload failure will destroy the robustness of controllability for the whole network. Therefore, the optimization of the robustness of interdependent network controllability is of great importance in the research area of complex networks. In this paper, based on the model of interdependent networks constructed first, we determine the cascading process under different proportions of node attacks. Then, the structural controllability of interdependent networks is measured by the minimum driver nodes. Furthermore, we propose a parameter which can be obtained by the structure and minimum driver set of interdependent networks under different proportions of node attacks and analyze the robustness for interdependent network controllability. Finally, we optimize the robustness of interdependent network controllability by redundant design including node backup and redundancy edge backup and improve the redundant design by proposing different strategies according to their cost. Comparative strategies of redundant design are conducted to find the best strategy. Results shows that node backup and redundancy edge backup can indeed decrease those nodes suffering from failure and improve the robustness of controllability. Considering the cost of redundant design, we should choose BBS (betweenness-based strategy or DBS (degree based strategy for node backup and HDF(high degree first for redundancy edge backup. Above all, our proposed strategies are feasible and effective at improving the robustness of interdependent network controllability.

  9. Synchronization criterion for Lur'e type complex dynamical networks with time-varying delay

    International Nuclear Information System (INIS)

    Ji, D.H.; Park, Ju H.; Yoo, W.J.; Won, S.C.; Lee, S.M.

    2010-01-01

    In this Letter, the synchronization problem for a class of complex dynamical networks in which every identical node is a Lur'e system with time-varying delay is considered. A delay-dependent synchronization criterion is derived for the synchronization of complex dynamical network that represented by Lur'e system with sector restricted nonlinearities. The derived criterion is a sufficient condition for absolute stability of error dynamics between the each nodes and the isolated node. Using a convex representation of the nonlinearity for error dynamics, the stability condition based on the discretized Lyapunov-Krasovskii functional is obtained via LMI formulation. The proposed delay-dependent synchronization criterion is less conservative than the existing ones. The effectiveness of our work is verified through numerical examples.

  10. On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

    Science.gov (United States)

    Chen, Bor-Sen; Lin, Ying-Po

    2011-01-01

    In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

  11. Fractional order control and synchronization of chaotic systems

    CERN Document Server

    Vaidyanathan, Sundarapandian; Ouannas, Adel

    2017-01-01

    The book reports on the latest advances in and applications of fractional order control and synchronization of chaotic systems, explaining the concepts involved in a clear, matter-of-fact style. It consists of 30 original contributions written by eminent scientists and active researchers in the field that address theories, methods and applications in a number of research areas related to fractional order control and synchronization of chaotic systems, such as: fractional chaotic systems, hyperchaotic systems, complex systems, fractional order discrete chaotic systems, chaos control, chaos synchronization, jerk circuits, fractional chaotic systems with hidden attractors, neural network, fuzzy logic controllers, behavioral modeling, robust and adaptive control, sliding mode control, different types of synchronization, circuit realization of chaotic systems, etc. In addition to providing readers extensive information on chaos fundamentals, fractional calculus, fractional differential equations, fractional contro...

  12. Synchronization stability and pattern selection in a memristive neuronal network

    Science.gov (United States)

    Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

    2017-11-01

    Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

  13. Synchronization stability and pattern selection in a memristive neuronal network.

    Science.gov (United States)

    Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

    2017-11-01

    Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

  14. Collective frequency variation in network synchronization and reverse PageRank.

    Science.gov (United States)

    Skardal, Per Sebastian; Taylor, Dane; Sun, Jie; Arenas, Alex

    2016-04-01

    A wide range of natural and engineered phenomena rely on large networks of interacting units to reach a dynamical consensus state where the system collectively operates. Here we study the dynamics of self-organizing systems and show that for generic directed networks the collective frequency of the ensemble is not the same as the mean of the individuals' natural frequencies. Specifically, we show that the collective frequency equals a weighted average of the natural frequencies, where the weights are given by an outflow centrality measure that is equivalent to a reverse PageRank centrality. Our findings uncover an intricate dependence of the collective frequency on both the structural directedness and dynamical heterogeneity of the network, and also reveal an unexplored connection between synchronization and PageRank, which opens the possibility of applying PageRank optimization to synchronization. Finally, we demonstrate the presence of collective frequency variation in real-world networks by considering the UK and Scandinavian power grids.

  15. Collective frequency variation in network synchronization and reverse PageRank

    Science.gov (United States)

    Skardal, Per Sebastian; Taylor, Dane; Sun, Jie; Arenas, Alex

    2016-04-01

    A wide range of natural and engineered phenomena rely on large networks of interacting units to reach a dynamical consensus state where the system collectively operates. Here we study the dynamics of self-organizing systems and show that for generic directed networks the collective frequency of the ensemble is not the same as the mean of the individuals' natural frequencies. Specifically, we show that the collective frequency equals a weighted average of the natural frequencies, where the weights are given by an outflow centrality measure that is equivalent to a reverse PageRank centrality. Our findings uncover an intricate dependence of the collective frequency on both the structural directedness and dynamical heterogeneity of the network, and also reveal an unexplored connection between synchronization and PageRank, which opens the possibility of applying PageRank optimization to synchronization. Finally, we demonstrate the presence of collective frequency variation in real-world networks by considering the UK and Scandinavian power grids.

  16. Network synchronization: optimal and pessimal scale-free topologies

    International Nuclear Information System (INIS)

    Donetti, Luca; Hurtado, Pablo I; Munoz, Miguel A

    2008-01-01

    By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability

  17. On the synchronization of neural networks containing time-varying delays and sector nonlinearity

    International Nuclear Information System (INIS)

    Yan, J.-J.; Lin, J.-S.; Hung, M.-L.; Liao, T.-L.

    2007-01-01

    We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The supplementary requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme

  18. Robustness of the ATLAS pixel clustering neural network algorithm

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00407780; The ATLAS collaboration

    2016-01-01

    Proton-proton collisions at the energy frontier puts strong constraints on track reconstruction algorithms. In the ATLAS track reconstruction algorithm, an artificial neural network is utilised to identify and split clusters of neighbouring read-out elements in the ATLAS pixel detector created by multiple charged particles. The robustness of the neural network algorithm is presented, probing its sensitivity to uncertainties in the detector conditions. The robustness is studied by evaluating the stability of the algorithm's performance under a range of variations in the inputs to the neural networks. Within reasonable variation magnitudes, the neural networks prove to be robust to most variation types.

  19. Adaptive coupling optimized spiking coherence and synchronization in Newman-Watts neuronal networks.

    Science.gov (United States)

    Gong, Yubing; Xu, Bo; Wu, Ya'nan

    2013-09-01

    In this paper, we have numerically studied the effect of adaptive coupling on the temporal coherence and synchronization of spiking activity in Newman-Watts Hodgkin-Huxley neuronal networks. It is found that random shortcuts can enhance the spiking synchronization more rapidly when the increment speed of adaptive coupling is increased and can optimize the temporal coherence of spikes only when the increment speed of adaptive coupling is appropriate. It is also found that adaptive coupling strength can enhance the synchronization of spikes and can optimize the temporal coherence of spikes when random shortcuts are appropriate. These results show that adaptive coupling has a big influence on random shortcuts related spiking activity and can enhance and optimize the temporal coherence and synchronization of spiking activity of the network. These findings can help better understand the roles of adaptive coupling for improving the information processing and transmission in neural systems.

  20. Emergence of structural patterns out of synchronization in networks with competitive interactions

    Science.gov (United States)

    Assenza, Salvatore; Gutiérrez, Ricardo; Gómez-Gardeñes, Jesús; Latora, Vito; Boccaletti, Stefano

    2011-09-01

    Synchronization is a collective phenomenon occurring in systems of interacting units, and is ubiquitous in nature, society and technology. Recent studies have enlightened the important role played by the interaction topology on the emergence of synchronized states. However, most of these studies neglect that real world systems change their interaction patterns in time. Here, we analyze synchronization features in networks in which structural and dynamical features co-evolve. The feedback of the node dynamics on the interaction pattern is ruled by the competition of two mechanisms: homophily (reinforcing those interactions with other correlated units in the graph) and homeostasis (preserving the value of the input strength received by each unit). The competition between these two adaptive principles leads to the emergence of key structural properties observed in real world networks, such as modular and scale-free structures, together with a striking enhancement of local synchronization in systems with no global order.

  1. Synchronization and desynchronization in a network of locally coupled Wilson-Cowan oscillators.

    Science.gov (United States)

    Campbell, S; Wang, D

    1996-01-01

    A network of Wilson-Cowan (WC) oscillators is constructed, and its emergent properties of synchronization and desynchronization are investigated by both computer simulation and formal analysis. The network is a 2D matrix, where each oscillator is coupled only to its neighbors. We show analytically that a chain of locally coupled oscillators (the piecewise linear approximation to the WC oscillator) synchronizes, and we present a technique to rapidly entrain finite numbers of oscillators. The coupling strengths change on a fast time scale based on a Hebbian rule. A global separator is introduced which receives input from and sends feedback to each oscillator in the matrix. The global separator is used to desynchronize different oscillator groups. Unlike many other models, the properties of this network emerge from local connections that preserve spatial relationships among components and are critical for encoding Gestalt principles of feature grouping. The ability to synchronize and desynchronize oscillator groups within this network offers a promising approach for pattern segmentation and figure/ground segregation based on oscillatory correlation.

  2. Stability, gain, and robustness in quantum feedback networks

    International Nuclear Information System (INIS)

    D'Helon, C.; James, M. R.

    2006-01-01

    In this paper we are concerned with the problem of stability for quantum feedback networks. We demonstrate in the context of quantum optics how stability of quantum feedback networks can be guaranteed using only simple gain inequalities for network components and algebraic relationships determined by the network. Quantum feedback networks are shown to be stable if the loop gain is less than one--this is an extension of the famous small gain theorem of classical control theory. We illustrate the simplicity and power of the small gain approach with applications to important problems of robust stability and robust stabilization

  3. Optimal autaptic and synaptic delays enhanced synchronization transitions induced by each other in Newman–Watts neuronal networks

    International Nuclear Information System (INIS)

    Wang, Baoying; Gong, Yubing; Xie, Huijuan; Wang, Qi

    2016-01-01

    Highlights: • Optimal autaptic delay enhanced synchronization transitions induced by synaptic delay in neuronal networks. • Optimal synaptic delay enhanced synchronization transitions induced by autaptic delay. • Optimal coupling strength enhanced synchronization transitions induced by autaptic or synaptic delay. - Abstract: In this paper, we numerically study the effect of electrical autaptic and synaptic delays on synchronization transitions induced by each other in Newman–Watts Hodgkin–Huxley neuronal networks. It is found that the synchronization transitions induced by synaptic delay vary with varying autaptic delay and become strongest when autaptic delay is optimal. Similarly, the synchronization transitions induced by autaptic delay vary with varying synaptic delay and become strongest at optimal synaptic delay. Also, there is optimal coupling strength by which the synchronization transitions induced by either synaptic or autaptic delay become strongest. These results show that electrical autaptic and synaptic delays can enhance synchronization transitions induced by each other in the neuronal networks. This implies that electrical autaptic and synaptic delays can cooperate with each other and more efficiently regulate the synchrony state of the neuronal networks. These findings could find potential implications for the information transmission in neural systems.

  4. Linear-control-based synchronization of coexisting attractor networks with time delays

    International Nuclear Information System (INIS)

    Yun-Zhong, Song

    2010-01-01

    This paper introduces the concept of linear-control-based synchronization of coexisting attractor networks with time delays. Within the new framework, closed loop control for each dynamic node is realized through linear state feedback around its own arena in a decentralized way, where the feedback matrix is determined through consideration of the coordination of the node dynamics, the inner connected matrix and the outer connected matrix. Unlike previously existing results, the feedback gain matrix here is decoupled from the inner matrix; this not only guarantees the flexible choice of the gain matrix, but also leaves much space for inner matrix configuration. Synchronization of coexisting attractor networks with time delays is made possible in virtue of local interaction, which works in a distributed way between individual neighbours, and the linear feedback control for each node. Provided that the network is connected and balanced, synchronization will come true naturally, where theoretical proof is given via a Lyapunov function. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme. (general)

  5. Quantifying the robustness of metro networks

    NARCIS (Netherlands)

    Wang, X.; Koç, Y.; Derrible, S.; Nasir Ahmad, Sk.; Kooij, R.E.

    2015-01-01

    Metros (heavy rail transit systems) are integral parts of urban transportation systems. Failures in their operations can have serious impacts on urban mobility, and measuring their robustness is therefore critical. Moreover, as physical networks, metros can be viewed as network topological entities,

  6. New results for global exponential synchronization in neural networks via functional differential inclusions.

    Science.gov (United States)

    Wang, Dongshu; Huang, Lihong; Tang, Longkun

    2015-08-01

    This paper is concerned with the synchronization dynamical behaviors for a class of delayed neural networks with discontinuous neuron activations. Continuous and discontinuous state feedback controller are designed such that the neural networks model can realize exponential complete synchronization in view of functional differential inclusions theory, Lyapunov functional method and inequality technique. The new proposed results here are very easy to verify and also applicable to neural networks with continuous activations. Finally, some numerical examples show the applicability and effectiveness of our main results.

  7. Analysis of Distributed Consensus Time Synchronization with Gaussian Delay over Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiong Gang

    2009-01-01

    Full Text Available This paper presents theoretical results on the convergence of the distributed consensus timing synchronization (DCTS algorithm for wireless sensor networks assuming general Gaussian delay between nodes. The asymptotic expectation and mean square of the global synchronization error are computed. The results lead to the definition of a time delay balanced network in which average timing consensus between nodes can be achieved despite random delays. Several structured network architectures are studied as examples, and their associated simulation results are used to validate analytical findings.

  8. Broad-scale small-world network topology induces optimal synchronization of flexible oscillators

    International Nuclear Information System (INIS)

    Markovič, Rene; Gosak, Marko; Marhl, Marko

    2014-01-01

    The discovery of small-world and scale-free properties of many man-made and natural complex networks has attracted increasing attention. Of particular interest is how the structural properties of a network facilitate and constrain its dynamical behavior. In this paper we study the synchronization of weakly coupled limit-cycle oscillators in dependence on the network topology as well as the dynamical features of individual oscillators. We show that flexible oscillators, characterized by near zero values of divergence, express maximal correlation in broad-scale small-world networks, whereas the non-flexible (rigid) oscillators are best correlated in more heterogeneous scale-free networks. We found that the synchronization behavior is governed by the interplay between the networks global efficiency and the mutual frequency adaptation. The latter differs for flexible and rigid oscillators. The results are discussed in terms of evolutionary advantages of broad-scale small-world networks in biological systems

  9. Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios

    DEFF Research Database (Denmark)

    Manzano, M.; Marzo, J. L.; Calle, E.

    2012-01-01

    on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....

  10. Traffic signal synchronization in the saturated high-density grid road network.

    Science.gov (United States)

    Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

    2015-01-01

    Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

  11. Exponential H(infinity) synchronization of general discrete-time chaotic neural networks with or without time delays.

    Science.gov (United States)

    Qi, Donglian; Liu, Meiqin; Qiu, Meikang; Zhang, Senlin

    2010-08-01

    This brief studies exponential H(infinity) synchronization of a class of general discrete-time chaotic neural networks with external disturbance. On the basis of the drive-response concept and H(infinity) control theory, and using Lyapunov-Krasovskii (or Lyapunov) functional, state feedback controllers are established to not only guarantee exponential stable synchronization between two general chaotic neural networks with or without time delays, but also reduce the effect of external disturbance on the synchronization error to a minimal H(infinity) norm constraint. The proposed controllers can be obtained by solving the convex optimization problems represented by linear matrix inequalities. Most discrete-time chaotic systems with or without time delays, such as Hopfield neural networks, cellular neural networks, bidirectional associative memory networks, recurrent multilayer perceptrons, Cohen-Grossberg neural networks, Chua's circuits, etc., can be transformed into this general chaotic neural network to be H(infinity) synchronization controller designed in a unified way. Finally, some illustrated examples with their simulations have been utilized to demonstrate the effectiveness of the proposed methods.

  12. Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks.

    Science.gov (United States)

    Tejedor, Alejandro; Longjas, Anthony; Zaliapin, Ilya; Ambroj, Samuel; Foufoula-Georgiou, Efi

    2017-08-17

    Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.

  13. Synchronization control of Hodgkin-Huxley neurons exposed to ELF electric field

    International Nuclear Information System (INIS)

    Che Yanqiu; Wang Jiang; Zhou Sisi; Deng Bin

    2009-01-01

    This paper presents an adaptive neural network H ∞ control for unidirectional synchronization of modified Hodgkin-Huxley (HH) neurons exposed to extremely low frequency (ELF) electric field. The proposed modified HH neurons exhibit periodic and chaotic dynamics in response to sinusoidal electric field stimulation. Based on the Lyapunov stability theory, we derive the updated laws of neural network for approximating the nonlinear uncertain functions of the error dynamical system. The H ∞ design technique makes the controller robust to unmodeled dynamics, disturbances and approximate errors. The proposed controller not only ensures closed-loop stability, but also guarantees an H ∞ performance for the synchronization error system. The states of the controlled slave system exponentially synchronize with that of the master one after control. The simulation results demonstrate the validity of the proposed method.

  14. Mixed H ∞ and Passive Projective Synchronization for Fractional Order Memristor-Based Neural Networks with Time-Delay and Parameter Uncertainty

    International Nuclear Information System (INIS)

    Song Xiao-Na; Song Shuai; Liu Lei-Po; Tejado Balsera, Inés

    2017-01-01

    This paper investigates the mixed H ∞ and passive projective synchronization problem for fractional-order (FO) memristor-based neural networks. Our aim is to design a controller such that, though the unavoidable phenomena of time-delay and parameter uncertainty are fully considered, the resulting closed-loop system is asymptotically stable with a mixed H ∞ and passive performance level. By combining active and adaptive control methods, a novel hybrid control strategy is designed, which can guarantee the robust stability of the closed-loop system and also ensure a mixed H ∞ and passive performance level. Via the application of FO Lyapunov stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequality techniques. Finally, two simulation examples are given to illustrate the effectiveness of the proposed method. (paper)

  15. Design of Robust Neural Network Classifiers

    DEFF Research Database (Denmark)

    Larsen, Jan; Andersen, Lars Nonboe; Hintz-Madsen, Mads

    1998-01-01

    This paper addresses a new framework for designing robust neural network classifiers. The network is optimized using the maximum a posteriori technique, i.e., the cost function is the sum of the log-likelihood and a regularization term (prior). In order to perform robust classification, we present...... a modified likelihood function which incorporates the potential risk of outliers in the data. This leads to the introduction of a new parameter, the outlier probability. Designing the neural classifier involves optimization of network weights as well as outlier probability and regularization parameters. We...... suggest to adapt the outlier probability and regularisation parameters by minimizing the error on a validation set, and a simple gradient descent scheme is derived. In addition, the framework allows for constructing a simple outlier detector. Experiments with artificial data demonstrate the potential...

  16. Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay

    International Nuclear Information System (INIS)

    Mei, Sun; Chang-Yan, Zeng; Li-Xin, Tian

    2009-01-01

    Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand–supply of energy resource in some regions of China

  17. Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay

    Science.gov (United States)

    Sun, Mei; Zeng, Chang-Yan; Tian, Li-Xin

    2009-01-01

    Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand-supply of energy resource in some regions of China.

  18. How optimal synchronization of oscillators depends on the network structure and the individual dynamical properties of the oscillators

    International Nuclear Information System (INIS)

    Markovic, R; Gosak, M; Marhl, M

    2013-01-01

    The problem of making a network of dynamical systems synchronize onto a common evolution is the subject of much ongoing research in several scientific disciplines. It is nowadays a well-known fact that the synchronization processes are gradually influenced by the interaction topology between the dynamically interacting units. A complex coupling configuration can significantly affect the synchronization abilities of a networked system. However, the question arises what is the optimal network topology that provides enhancement of the synchronization features under given circumstances. In order to address this issue we make use of a network model in which we can smoothly tune the topology from a highly heterogeneous and efficient scale-free network to a homogeneous and less efficient network. The network is then populated with Poincaré oscillators, a paradigmatic model for limit-cycle oscillations. This oscillator model exhibits a parameter that enables changes of the limit cycle attraction and is thus immediately related to flexibility/rigidity properties of the oscillator. Our results reveal that for weak attractions of the limit cycle, intermediate homogeneous topology ensures maximal synchronization, whereas highly heterogeneous scale-free topology ensures maximal synchronization for strong attractions of the limit cycle. We argue that the flexibility/rigidity of individual nodes of the networks defines the topology, where maximal global coherence is achieved.

  19. How single node dynamics enhances synchronization in neural networks with electrical coupling

    International Nuclear Information System (INIS)

    Bonacini, E.; Burioni, R.; Di Volo, M.; Groppi, M.; Soresina, C.; Vezzani, A.

    2016-01-01

    The stability of the completely synchronous state in neural networks with electrical coupling is analytically investigated applying both the Master Stability Function approach (MSF), developed by Pecora and Carroll (1998), and the Connection Graph Stability method (CGS) proposed by Belykh et al. (2004). The local dynamics is described by Morris–Lecar model for spiking neurons and by Hindmarsh–Rose model in spike, burst, irregular spike and irregular burst regimes. The combined application of both CGS and MSF methods provides an efficient estimate of the synchronization thresholds, namely bounds for the coupling strength ranges in which the synchronous state is stable. In all the considered cases, we observe that high values of coupling strength tend to synchronize the system. Furthermore, we observe a correlation between the single node attractor and the local stability properties given by MSF. The analytical results are compared with numerical simulations on a sample network, with excellent agreement.

  20. Network synchronization: optimal and pessimal scale-free topologies

    Energy Technology Data Exchange (ETDEWEB)

    Donetti, Luca [Departamento de Electronica y Tecnologia de Computadores and Instituto de Fisica Teorica y Computacional Carlos I, Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain); Hurtado, Pablo I; Munoz, Miguel A [Departamento de Electromagnetismo y Fisica de la Materia and Instituto Carlos I de Fisica Teorica y Computacional Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain)], E-mail: mamunoz@onsager.ugr.es

    2008-06-06

    By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability.

  1. Robust quantum network architectures and topologies for entanglement distribution

    Science.gov (United States)

    Das, Siddhartha; Khatri, Sumeet; Dowling, Jonathan P.

    2018-01-01

    Entanglement distribution is a prerequisite for several important quantum information processing and computing tasks, such as quantum teleportation, quantum key distribution, and distributed quantum computing. In this work, we focus on two-dimensional quantum networks based on optical quantum technologies using dual-rail photonic qubits for the building of a fail-safe quantum internet. We lay out a quantum network architecture for entanglement distribution between distant parties using a Bravais lattice topology, with the technological constraint that quantum repeaters equipped with quantum memories are not easily accessible. We provide a robust protocol for simultaneous entanglement distribution between two distant groups of parties on this network. We also discuss a memory-based quantum network architecture that can be implemented on networks with an arbitrary topology. We examine networks with bow-tie lattice and Archimedean lattice topologies and use percolation theory to quantify the robustness of the networks. In particular, we provide figures of merit on the loss parameter of the optical medium that depend only on the topology of the network and quantify the robustness of the network against intermittent photon loss and intermittent failure of nodes. These figures of merit can be used to compare the robustness of different network topologies in order to determine the best topology in a given real-world scenario, which is critical in the realization of the quantum internet.

  2. Synchronization enhancement via an oscillatory bath in a network of ...

    Indian Academy of Sciences (India)

    2015-02-05

    Feb 5, 2015 ... The possibility of using a dynamic environment to achieve and optimize phase synchronization in a network of self-excited cells with free-end boundary conditions is addressed in this paper. The dynamic environment is an oscillatory bath coupled linearly to a network of four cells. The boundaries of the ...

  3. Complete synchronization condition in a network of piezoelectric micro-beam

    International Nuclear Information System (INIS)

    Taffoti Yolong, V.Y.; Woafo, P.

    2007-10-01

    This work deals with the dynamics of a network of piezoelectric micro-beams. The complete synchronization condition for this class of chaotic nonlinear electromechanical systems devices with nearest-neighbor diffusive coupling is studied. The nonlinearities on the device studied here are both on the electrical component and on the mechanical one. The investigation is made for the case of a large number of discrete piezoelectric disks coupled. The problem of chaos synchronization is described and converted into the analysis of stability of the system via its differential equations. We show that the complete synchronization of N identical coupled nonlinear chaotic systems having the shift invariant coupling schemes can be calculated from the synchronization of two of them coupled in both directions. According to analytical, semi-analytical predictions and numerical calculations, the transition boundaries for chaos synchronization state in the coupled system are determined as a function of the increasing number of oscillators. (author)

  4. Robustness analysis of interdependent networks under multiple-attacking strategies

    Science.gov (United States)

    Gao, Yan-Li; Chen, Shi-Ming; Nie, Sen; Ma, Fei; Guan, Jun-Jie

    2018-04-01

    The robustness of complex networks under attacks largely depends on the structure of a network and the nature of the attacks. Previous research on interdependent networks has focused on two types of initial attack: random attack and degree-based targeted attack. In this paper, a deliberate attack function is proposed, where six kinds of deliberate attacking strategies can be derived by adjusting the tunable parameters. Moreover, the robustness of four types of interdependent networks (BA-BA, ER-ER, BA-ER and ER-BA) with different coupling modes (random, positive and negative correlation) is evaluated under different attacking strategies. Interesting conclusions could be obtained. It can be found that the positive coupling mode can make the vulnerability of the interdependent network to be absolutely dependent on the most vulnerable sub-network under deliberate attacks, whereas random and negative coupling modes make the vulnerability of interdependent network to be mainly dependent on the being attacked sub-network. The robustness of interdependent network will be enhanced with the degree-degree correlation coefficient varying from positive to negative. Therefore, The negative coupling mode is relatively more optimal than others, which can substantially improve the robustness of the ER-ER network and ER-BA network. In terms of the attacking strategies on interdependent networks, the degree information of node is more valuable than the betweenness. In addition, we found a more efficient attacking strategy for each coupled interdependent network and proposed the corresponding protection strategy for suppressing cascading failure. Our results can be very useful for safety design and protection of interdependent networks.

  5. Stability and synchronization control of stochastic neural networks

    CERN Document Server

    Zhou, Wuneng; Zhou, Liuwei; Tong, Dongbing

    2016-01-01

    This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks who wish to learn the core principles, methods, algorithms and applications of SNN.

  6. Degree of synchronization modulated by inhibitory neurons in clustered excitatory-inhibitory recurrent networks

    Science.gov (United States)

    Li, Huiyan; Sun, Xiaojuan; Xiao, Jinghua

    2018-01-01

    An excitatory-inhibitory recurrent neuronal network is established to numerically study the effect of inhibitory neurons on the synchronization degree of neuronal systems. The obtained results show that, with the number of inhibitory neurons and the coupling strength from an inhibitory neuron to an excitatory neuron increasing, inhibitory neurons can not only reduce the synchronization degree when the synchronization degree of the excitatory population is initially higher, but also enhance it when it is initially lower. Meanwhile, inhibitory neurons could also help the neuronal networks to maintain moderate synchronized states. In this paper, we call this effect as modulation effect of inhibitory neurons. With the obtained results, it is further revealed that the ratio of excitatory neurons to inhibitory neurons being nearly 4 : 1 is an economic and affordable choice for inhibitory neurons to realize this modulation effect.

  7. Complex Projective Synchronization in Drive-Response Stochastic Complex Networks by Impulsive Pinning Control

    Directory of Open Access Journals (Sweden)

    Xuefei Wu

    2014-01-01

    Full Text Available The complex projective synchronization in drive-response stochastic coupled networks with complex-variable systems is considered. The impulsive pinning control scheme is adopted to achieve complex projective synchronization and several simple and practical sufficient conditions are obtained in a general drive-response network. In addition, the adaptive feedback algorithms are proposed to adjust the control strength. Several numerical simulations are provided to show the effectiveness and feasibility of the proposed methods.

  8. Outer Synchronization between Two Coupled Complex Networks and Its Application in Public Traffic Supernetwork

    Directory of Open Access Journals (Sweden)

    Wen-ju Du

    2016-01-01

    Full Text Available The paper presents a new urban public traffic supernetwork model by using the existing bus network modeling method, consisting of the conventional bus traffic network and the urban rail traffic network. We investigate the synchronization problem of urban public traffic supernetwork model by using the coupled complex network’s outer synchronization theory. Analytical and numerical simulations are given to illustrate the impact of traffic dispatching frequency and traffic lines optimization to the urban public traffic supernetwork balance.

  9. Coherence Resonance and Noise-Induced Synchronization in Hindmarsh-Rose Neural Network with Different Topologies

    International Nuclear Information System (INIS)

    Wei Duqu; Luo Xiaoshu

    2007-01-01

    In this paper, we investigate coherence resonance (CR) and noise-induced synchronization in Hindmarsh-Rose (HR) neural network with three different types of topologies: regular, random, and small-world. It is found that the additive noise can induce CR in HR neural network with different topologies and its coherence is optimized by a proper noise level. It is also found that as coupling strength increases the plateau in the measure of coherence curve becomes broadened and the effects of network topology is more pronounced simultaneously. Moreover, we find that increasing the probability p of the network topology leads to an enhancement of noise-induced synchronization in HR neurons network.

  10. Synchronization from Second Order Network Connectivity Statistics

    Science.gov (United States)

    Zhao, Liqiong; Beverlin, Bryce; Netoff, Theoden; Nykamp, Duane Q.

    2011-01-01

    We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections, and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by their increasing the effective coupling strength. The decrease of synchrony with convergent connections is primarily due to the resulting heterogeneity in firing rates. PMID:21779239

  11. Detecting phase synchronization by localized maps: Application to neural networks

    OpenAIRE

    Pereira, T.; Baptista, M. S.; Kurths, J.

    2007-01-01

    We present an approach which enables to state about the existence of phase synchronization in coupled chaotic oscillators without having to measure the phase. This is done by observing the oscillators at special times, and analyzing whether this set of points is localized. In particular, we show that this approach is fruitful to analyze the onset of phase synchronization in chaotic attractors whose phases are not well defined, as well as, in networks of non-identical spiking/bursting neurons ...

  12. On business cycles synchronization in Europe: A note on network analysis

    Science.gov (United States)

    Matesanz, David; Ortega, Guillermo J.

    2016-11-01

    In this paper we examine synchronization in European business cycles from 1950 to 2013. Herein we further investigate previous and controversial results that arise from complex network analysis of this topic. By focusing on the importance of different configurations in the commonly used rolling windows and threshold significance levels, we find that selections are critical to obtaining accurate networks. Output co-movement and connectivity show no appreciable changes during the beginning of the Euro period, but rather dramatic jumps are observed since the outbreak of the global financial crisis. At this time, previous lead/lag effects disappeared and in-phase synchronization across Europe was observed.

  13. Lag Synchronization Between Two Coupled Networks via Open-Plus-Closed-Loop and Adaptive Controls

    International Nuclear Information System (INIS)

    Tong-Chun Hu; Yong-Qing Wu; Shi-Xing Li

    2016-01-01

    In this paper, we study lag synchronization between two coupled networks and apply two types of control schemes, including the open-plus-closed-loop (OPCL) and adaptive controls. We then design the corresponding control algorithms according to the OPCL and adaptive feedback schemes. With the designed controllers, we obtain two theorems on the lag synchronization based on Lyapunov stability theory and Barbalat's lemma. Finally we provide numerical examples to show the effectiveness of the obtained controllers and see that the adaptive control is stronger than the OPCL control when realizing the lag synchronization between two coupled networks with different coupling structures. (paper)

  14. Centrality Robustness and Link Prediction in Complex Social Networks

    DEFF Research Database (Denmark)

    Davidsen, Søren Atmakuri; Ortiz-Arroyo, Daniel

    2012-01-01

    . Secondly, we present a method to predict edges in dynamic social networks. Our experimental results indicate that the robustness of the centrality measures applied to more realistic social networks follows a predictable pattern and that the use of temporal statistics could improve the accuracy achieved......This chapter addresses two important issues in social network analysis that involve uncertainty. Firstly, we present am analysis on the robustness of centrality measures that extend the work presented in Borgati et al. using three types of complex network structures and one real social network...

  15. Attack robustness and centrality of complex networks.

    Directory of Open Access Journals (Sweden)

    Swami Iyer

    Full Text Available Many complex systems can be described by networks, in which the constituent components are represented by vertices and the connections between the components are represented by edges between the corresponding vertices. A fundamental issue concerning complex networked systems is the robustness of the overall system to the failure of its constituent parts. Since the degree to which a networked system continues to function, as its component parts are degraded, typically depends on the integrity of the underlying network, the question of system robustness can be addressed by analyzing how the network structure changes as vertices are removed. Previous work has considered how the structure of complex networks change as vertices are removed uniformly at random, in decreasing order of their degree, or in decreasing order of their betweenness centrality. Here we extend these studies by investigating the effect on network structure of targeting vertices for removal based on a wider range of non-local measures of potential importance than simply degree or betweenness. We consider the effect of such targeted vertex removal on model networks with different degree distributions, clustering coefficients and assortativity coefficients, and for a variety of empirical networks.

  16. Effect of interaction strength on robustness of controlling edge dynamics in complex networks

    Science.gov (United States)

    Pang, Shao-Peng; Hao, Fei

    2018-05-01

    Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.

  17. Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

    Science.gov (United States)

    Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

    2017-04-01

    Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

  18. Advanced neural network-based computational schemes for robust fault diagnosis

    CERN Document Server

    Mrugalski, Marcin

    2014-01-01

    The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practica...

  19. Time Delay and Long-Range Connection Induced Synchronization Transitions in Newman-Watts Small-World Neuronal Networks

    Science.gov (United States)

    Qian, Yu

    2014-01-01

    The synchronization transitions in Newman-Watts small-world neuronal networks (SWNNs) induced by time delay and long-range connection (LRC) probability have been investigated by synchronization parameter and space-time plots. Four distinct parameter regions, that is, asynchronous region, transition region, synchronous region, and oscillatory region have been discovered at certain LRC probability as time delay is increased. Interestingly, desynchronization is observed in oscillatory region. More importantly, we consider the spatiotemporal patterns obtained in delayed Newman-Watts SWNNs are the competition results between long-range drivings (LRDs) and neighboring interactions. In addition, for moderate time delay, the synchronization of neuronal network can be enhanced remarkably by increasing LRC probability. Furthermore, lag synchronization has been found between weak synchronization and complete synchronization as LRC probability is a little less than 1.0. Finally, the two necessary conditions, moderate time delay and large numbers of LRCs, are exposed explicitly for synchronization in delayed Newman-Watts SWNNs. PMID:24810595

  20. Structural and robustness properties of smart-city transportation networks

    International Nuclear Information System (INIS)

    Zhang Zhen-Gang; Ding Zhuo; Fan Jing-Fang; Chen Xiao-Song; Meng Jun; Ye Fang-Fu; Ding Yi-Min

    2015-01-01

    The concept of smart city gives an excellent resolution to construct and develop modern cities, and also demands infrastructure construction. How to build a safe, stable, and highly efficient public transportation system becomes an important topic in the process of city construction. In this work, we study the structural and robustness properties of transportation networks and their sub-networks. We introduce a complementary network model to study the relevance and complementarity between bus network and subway network. Our numerical results show that the mutual supplement of networks can improve the network robustness. This conclusion provides a theoretical basis for the construction of public traffic networks, and it also supports reasonable operation of managing smart cities. (rapid communication)

  1. Global impulsive exponential synchronization of stochastic perturbed chaotic delayed neural networks

    International Nuclear Information System (INIS)

    Hua-Guang, Zhang; Tie-Dong, Ma; Jie, Fu; Shao-Cheng, Tong

    2009-01-01

    In this paper, the global impulsive exponential synchronization problem of a class of chaotic delayed neural networks (DNNs) with stochastic perturbation is studied. Based on the Lyapunov stability theory, stochastic analysis approach and an efficient impulsive delay differential inequality, some new exponential synchronization criteria expressed in the form of the linear matrix inequality (LMI) are derived. The designed impulsive controller not only can globally exponentially stabilize the error dynamics in mean square, but also can control the exponential synchronization rate. Furthermore, to estimate the stable region of the synchronization error dynamics, a novel optimization control algorithm is proposed, which can deal with the minimum problem with two nonlinear terms coexisting in LMIs effectively. Simulation results finally demonstrate the effectiveness of the proposed method

  2. Consensus and Synchronization in Complex Networks

    CERN Document Server

    2013-01-01

    Synchronization in complex networks is one of the most captivating cooperative phenomena in nature and has been shown to be of fundamental importance in such varied circumstances as the continued existence of species, the functioning of heart pacemaker cells, epileptic seizures, neuronal firing in the feline visual cortex and cognitive tasks in humans. E.g. coupled visual and acoustic interactions make fireflies flash, crickets chirp, and an audience clap in unison. On the other hand, in distributed systems and networks, it is often necessary for some or all of the nodes to calculate some function of certain parameters, e.g. sink nodes in sensor networks being tasked with calculating the average measurement value of all the sensors or multi-agent systems in which all agents are required to coordinate their speed and direction. When all nodes calculate the same function of the initial values in the system, they are said to reach consensus. Such concepts - sometimes also called state agreement, rendezvous, and ...

  3. Dislocation Coupling-Induced Transition of Synchronization in Two-Layer Neuronal Networks

    International Nuclear Information System (INIS)

    Qin Hui-Xin; Ma Jun; Wang Chun-Ni; Jin Wu-Yin

    2014-01-01

    The mutual coupling between neurons in a realistic neuronal system is much complex, and a two-layer neuronal network is designed to investigate the transition of electric activities of neurons. The Hindmarsh—Rose neuron model is used to describe the local dynamics of each neuron, and neurons in the two-layer networks are coupled in dislocated type. The coupling intensity between two-layer networks, and the coupling ratio (Pro), which defines the percentage involved in the coupling in each layer, are changed to observe the synchronization transition of collective behaviors in the two-layer networks. It is found that the two-layer networks of neurons becomes synchronized with increasing the coupling intensity and coupling ratio (Pro) beyond certain thresholds. An ordered wave in the first layer is useful to wake up the rest state in the second layer, or suppress the spatiotemporal state in the second layer under coupling by generating target wave or spiral waves. And the scheme of dislocation coupling can be used to suppress spatiotemporal chaos and excite quiescent neurons. (interdisciplinary physics and related areas of science and technology)

  4. Distributed Synchronization in Networks of Agent Systems With Nonlinearities and Random Switchings.

    Science.gov (United States)

    Tang, Yang; Gao, Huijun; Zou, Wei; Kurths, Jürgen

    2013-02-01

    In this paper, the distributed synchronization problem of networks of agent systems with controllers and nonlinearities subject to Bernoulli switchings is investigated. Controllers and adaptive updating laws injected in each vertex of networks depend on the state information of its neighborhood. Three sets of Bernoulli stochastic variables are introduced to describe the occurrence probabilities of distributed adaptive controllers, updating laws and nonlinearities, respectively. By the Lyapunov functions method, we show that the distributed synchronization of networks composed of agent systems with multiple randomly occurring nonlinearities, multiple randomly occurring controllers, and multiple randomly occurring updating laws can be achieved in mean square under certain criteria. The conditions derived in this paper can be solved by semi-definite programming. Moreover, by mathematical analysis, we find that the coupling strength, the probabilities of the Bernoulli stochastic variables, and the form of nonlinearities have great impacts on the convergence speed and the terminal control strength. The synchronization criteria and the observed phenomena are demonstrated by several numerical simulation examples. In addition, the advantage of distributed adaptive controllers over conventional adaptive controllers is illustrated.

  5. Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillators

    Science.gov (United States)

    Papadopoulos, Lia; Kim, Jason Z.; Kurths, Jürgen; Bassett, Danielle S.

    2017-07-01

    Synchronization of non-identical oscillators coupled through complex networks is an important example of collective behavior, and it is interesting to ask how the structural organization of network interactions influences this process. Several studies have explored and uncovered optimal topologies for synchronization by making purposeful alterations to a network. On the other hand, the connectivity patterns of many natural systems are often not static, but are rather modulated over time according to their dynamics. However, this co-evolution and the extent to which the dynamics of the individual units can shape the organization of the network itself are less well understood. Here, we study initially randomly connected but locally adaptive networks of Kuramoto oscillators. In particular, the system employs a co-evolutionary rewiring strategy that depends only on the instantaneous, pairwise phase differences of neighboring oscillators, and that conserves the total number of edges, allowing the effects of local reorganization to be isolated. We find that a simple rule—which preserves connections between more out-of-phase oscillators while rewiring connections between more in-phase oscillators—can cause initially disordered networks to organize into more structured topologies that support enhanced synchronization dynamics. We examine how this process unfolds over time, finding a dependence on the intrinsic frequencies of the oscillators, the global coupling, and the network density, in terms of how the adaptive mechanism reorganizes the network and influences the dynamics. Importantly, for large enough coupling and after sufficient adaptation, the resulting networks exhibit interesting characteristics, including degree-frequency and frequency-neighbor frequency correlations. These properties have previously been associated with optimal synchronization or explosive transitions in which the networks were constructed using global information. On the contrary, by

  6. The mechanism of synchronization in feed-forward neuronal networks

    International Nuclear Information System (INIS)

    Goedeke, S; Diesmann, M

    2008-01-01

    Synchronization in feed-forward subnetworks of the brain has been proposed to explain the precisely timed spike patterns observed in experiments. While the attractor dynamics of these networks is now well understood, the underlying single neuron mechanisms remain unexplained. Previous attempts have captured the effects of the highly fluctuating membrane potential by relating spike intensity f(U) to the instantaneous voltage U generated by the input. This article shows that f is high during the rise and low during the decay of U(t), demonstrating that the U-dot-dependence of f, not refractoriness, is essential for synchronization. Moreover, the bifurcation scenario is quantitatively described by a simple f(U,U-dot) relationship. These findings suggest f(U,U-dot) as the relevant model class for the investigation of neural synchronization phenomena in a noisy environment

  7. Subthalamic stimulation modulates cortical motor network activity and synchronization in Parkinson’s disease

    Science.gov (United States)

    Klotz, Rosa; Govindan, Rathinaswamy B.; Scholten, Marlieke; Naros, Georgios; Ramos-Murguialday, Ander; Bunjes, Friedemann; Meisner, Christoph; Plewnia, Christian; Krüger, Rejko

    2015-01-01

    Dynamic modulations of large-scale network activity and synchronization are inherent to a broad spectrum of cognitive processes and are disturbed in neuropsychiatric conditions including Parkinson’s disease. Here, we set out to address the motor network activity and synchronization in Parkinson’s disease and its modulation with subthalamic stimulation. To this end, 20 patients with idiopathic Parkinson’s disease with subthalamic nucleus stimulation were analysed on externally cued right hand finger movements with 1.5-s interstimulus interval. Simultaneous recordings were obtained from electromyography on antagonistic muscles (right flexor digitorum and extensor digitorum) together with 64-channel electroencephalography. Time-frequency event-related spectral perturbations were assessed to determine cortical and muscular activity. Next, cross-spectra in the time-frequency domain were analysed to explore the cortico-cortical synchronization. The time-frequency modulations enabled us to select a time-frequency range relevant for motor processing. On these time-frequency windows, we developed an extension of the phase synchronization index to quantify the global cortico-cortical synchronization and to obtain topographic differentiations of distinct electrode sites with respect to their contributions to the global phase synchronization index. The spectral measures were used to predict clinical and reaction time outcome using regression analysis. We found that movement-related desynchronization of cortical activity in the upper alpha and beta range was significantly facilitated with ‘stimulation on’ compared to ‘stimulation off’ on electrodes over the bilateral parietal, sensorimotor, premotor, supplementary-motor, and prefrontal areas, including the bilateral inferior prefrontal areas. These spectral modulations enabled us to predict both clinical and reaction time improvement from subthalamic stimulation. With ‘stimulation on’, interhemispheric cortico

  8. Some scale-free networks could be robust under selective node attacks

    Science.gov (United States)

    Zheng, Bojin; Huang, Dan; Li, Deyi; Chen, Guisheng; Lan, Wenfei

    2011-04-01

    It is a mainstream idea that scale-free network would be fragile under the selective attacks. Internet is a typical scale-free network in the real world, but it never collapses under the selective attacks of computer viruses and hackers. This phenomenon is different from the deduction of the idea above because this idea assumes the same cost to delete an arbitrary node. Hence this paper discusses the behaviors of the scale-free network under the selective node attack with different cost. Through the experiments on five complex networks, we show that the scale-free network is possibly robust under the selective node attacks; furthermore, the more compact the network is, and the larger the average degree is, then the more robust the network is; with the same average degrees, the more compact the network is, the more robust the network is. This result would enrich the theory of the invulnerability of the network, and can be used to build robust social, technological and biological networks, and also has the potential to find the target of drugs.

  9. Tuning the synchronization of a network of weakly coupled self-oscillating gels via capacitors

    Science.gov (United States)

    Fang, Yan; Yashin, Victor V.; Dickerson, Samuel J.; Balazs, Anna C.

    2018-05-01

    We consider a network of coupled oscillating units, where each unit comprises a self-oscillating polymer gel undergoing the Belousov-Zhabotinsky (BZ) reaction and an overlaying piezoelectric (PZ) cantilever. Through chemo-mechano-electrical coupling, the oscillations of the networked BZ-PZ units achieve in-phase or anti-phase synchronization, enabling, for example, the storage of information within the system. Herein, we develop numerical and computational models to show that the introduction of capacitors into the BZ-PZ system enhances the dynamical behavior of the oscillating network by yielding additional stable synchronization modes. We specifically show that the capacitors lead to a redistribution of charge in the system and alteration of the force that the PZ cantilevers apply to the underlying gel. Hence, the capacitors modify the strength of the coupling between the oscillators in the network. We utilize a linear stability analysis to determine the phase behavior of BZ-PZ networks encompassing different capacitances, force polarities, and number of units and then verify our findings with numerical simulations. Thus, through analytical calculations and numerical simulations, we determine the impact of the capacitors on the existence of the synchronization modes, their stability, and the rate of synchronization within these complex dynamical systems. The findings from our study can be used to design robotic materials that harness the materials' intrinsic, responsive properties to perform such functions as sensing, actuation, and information storage.

  10. Methods for constructing time synchronous networks. Part 1. Consideration and experiment of time synchronizing functions and devices; Zenkei jikoku dokimo no kosei shuho. 1. Jikoku doki hoshiki no kino kento to jikkenteki kensho

    Energy Technology Data Exchange (ETDEWEB)

    Serizawa, Y.; Kitamura, K.; Myojin, M.; Shimizu, K. [Central Research Institute of Electric Power Industry, Tokyo (Japan); Nenohi, H.; Morimitsu, M.; Masui, O.; Matsushima, T. [NEC Corp., Tokyo (Japan)

    1996-03-01

    For the purpose of the back-up protection of regional power line system and the protection and control of accident influence, construction methods of time synchronizing network have been investigated. This paper proposes a method suitable for business power communication. For the synchronization between stations, transmission delay and its fluctuation have to be measured accurately by transmitting time signals between stations. Based on the observed delay values, the function of time correction (phase synchronizing control) of synchronized station is required. A mutual type synchronizing method was proposed, to which a sampling synchronization method of carrier relay system for transmission line protection was applied. In this method, transmission of time signals and measurement of delays are mutually conducted between stations, and phases of independent transmitters of the both stations are controlled so as to be equivalent. This method is characterized by the suppression of delays with fluctuation in the same direction of two-way transmission. For the transmission of time signals, two types of synchronizing devices were employed, i.e., synchronous and asynchronous manners. In the former, frequency synchronous network of SDH (synchronous digital hierarchy) was synchronized. In the latter, a carrier relay device was utilized independent of frequency synchronous network. It was expected that a synchronous network with an order of {mu}s can be constructed. 11 refs., 21 figs., 3 tabs.

  11. Experimental realization of synchronization in complex networks with Chua's circuits like nodes

    Energy Technology Data Exchange (ETDEWEB)

    Posadas-Castillo, C. [Engineering Faculty, Baja California Autonomous University (UABC), Km. 103, Carretera Tijuana-Ensenada, 22860 Ensenada, BC (Mexico); Engineering Mechanic and Electric Faculty of Nuevo Leon Autonomous University (UANL), Pedro de Alba, S.N., Cd. Universitaria, San Nicolas de los Garza, NL (Mexico); Cruz-Hernandez, C. [Electronics and Telecommunications Department, Scientific Research and Advanced Studies of Ensenada (CICESE), Km. 107, Carretera Tijuana-Ensenada, 22860 Ensenada, BC (Mexico)], E-mail: ccruz@cicese.mx; Lopez-Gutierrez, R.M. [Engineering Faculty, Baja California Autonomous University (UABC), Km. 103, Carretera Tijuana-Ensenada, 22860 Ensenada, BC (Mexico)

    2009-05-30

    In this paper, an experimental study on practical realization of synchronization in globally coupled networks with Chua's circuits like nodes is presented. Synchronization of coupled multiple Chua's circuits is achieved by appealing to results from complex systems theory. In particular, we design and implement electronically complex dynamical networks composed by three coupled Chua's circuits, considering two scenarios: (i) without master node, and (ii) with (periodic and chaotic) master node. The interactions in the networks are defined by coupling the first state of each Chua's circuit.

  12. Delay-range-dependent exponential H∞ synchronization of a class of delayed neural networks

    International Nuclear Information System (INIS)

    Karimi, Hamid Reza; Maass, Peter

    2009-01-01

    This article aims to present a multiple delayed state-feedback control design for exponential H ∞ synchronization problem of a class of delayed neural networks with multiple time-varying discrete delays. On the basis of the drive-response concept and by introducing a descriptor technique and using Lyapunov-Krasovskii functional, new delay-range-dependent sufficient conditions for exponential H ∞ synchronization of the drive-response structure of neural networks are driven in terms of linear matrix inequalities (LMIs). The explicit expression of the controller gain matrices are parameterized based on the solvability conditions such that the drive system and the response system can be exponentially synchronized. A numerical example is included to illustrate the applicability of the proposed design method.

  13. Correlated network of networks enhances robustness against catastrophic failures.

    Science.gov (United States)

    Min, Byungjoon; Zheng, Muhua

    2018-01-01

    Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way to enhance network robustness by manipulating connection patterns, along with other methods such as controlling the state of node based on a local rule.

  14. Robustness and Vulnerability of Networks with Dynamical Dependency Groups.

    Science.gov (United States)

    Bai, Ya-Nan; Huang, Ning; Wang, Lei; Wu, Zhi-Xi

    2016-11-28

    The dependency property and self-recovery of failure nodes both have great effects on the robustness of networks during the cascading process. Existing investigations focused mainly on the failure mechanism of static dependency groups without considering the time-dependency of interdependent nodes and the recovery mechanism in reality. In this study, we present an evolving network model consisting of failure mechanisms and a recovery mechanism to explore network robustness, where the dependency relations among nodes vary over time. Based on generating function techniques, we provide an analytical framework for random networks with arbitrary degree distribution. In particular, we theoretically find that an abrupt percolation transition exists corresponding to the dynamical dependency groups for a wide range of topologies after initial random removal. Moreover, when the abrupt transition point is above the failure threshold of dependency groups, the evolving network with the larger dependency groups is more vulnerable; when below it, the larger dependency groups make the network more robust. Numerical simulations employing the Erdős-Rényi network and Barabási-Albert scale free network are performed to validate our theoretical results.

  15. Timing subsystem development: Network synchronization experiments

    Science.gov (United States)

    Backe, K. R.

    1983-01-01

    This paper describes a program in which several experimental timing subsystem prototypes were designed, fabricated, and field tested using a small network of troposcatter and microwave digital communication links. This equipment was responsible for modem/radio interfacing, time interval measurement, clock adjustment and distribution, synchronization technique, and node to node information exchange. Presented are discussions of the design approach, measurement plan, and performance assessment methods. Recommendations are made based on the findings of the test program and an evaluation of the design of both the hardware and software elements of the timing subsystem prototypes.

  16. Successive lag synchronization on dynamical networks with communication delay

    International Nuclear Information System (INIS)

    Zhang Xin-Jian; Wei Ai-Ju; Li Ke-Zan

    2016-01-01

    In this paper, successive lag synchronization (SLS) on a dynamical network with communication delay is investigated. In order to achieve SLS on the dynamical network with communication delay, we design linear feedback control and adaptive control, respectively. By using the Lyapunov function method, we obtain some sufficient conditions for global stability of SLS. To verify these results, some numerical examples are further presented. This work may find potential applications in consensus of multi-agent systems. (paper)

  17. SynUTC - high precision time synchronization over ethernet networks

    CERN Document Server

    Höller, R; Horauer, M; Kerö, N; Schmid, U; Schossmaier, K

    2002-01-01

    This article describes our SynUTC (Synchronized Universal Time Coordinated) technology, which enables high-accuracy distribution of GPS time and time synchronization of network nodes connected via standard Ethernet LANs. By means of exchanging data packets in conjunction with moderate hardware support at nodes and switches, an overall worst-case accuracy in the range of some 100 ns can be achieved, with negligible communication overhead. Our technology thus improves the 1 ms-range accuracy achievable by conventional, software-based approaches like NTP by 4 orders of magnitude. Applications can use the high-accuracy global time provided by SynUTC for event timestamping and event generation both at hardware and software level. SynUTC is based upon inserting highly accurate time information into dedicated data packets at the media-independent interface (MII) between the physical layer transceiver and the network controller upon packet transmission and reception, respectively. As a consequence, every node has acc...

  18. Sensorless Speed Control of Permanent Magnet Synchronous Motors by Neural Network Algorithm

    Directory of Open Access Journals (Sweden)

    Ming-Shyan Wang

    2014-01-01

    Full Text Available The sliding mode control has the merits with respect to the variation of the disturbance and robustness. In this paper, the sensorless sliding-mode observer with least mean squared error approach for permanent magnet synchronous motor (PMSM to detect the rotor position by counter electromotive force and then compute motor speed is designed and implemented. In addition, the neural network control is also used to compensate the PI gain tuning to increase the speed accuracy without regarding the errors of the current measurement and motor noise. In this paper, a digital signal processor TMS320F2812 utilizes its high-speed ADC module to get current feedback information and thus to estimate the rotor position and takes advantage of the built-in modules to achieve SVPWM current control so that the senseless speed control will be accomplished. The correctness and effectiveness of the proposed control system will be verified from the experimental results.

  19. A combined video and synchronous VSAT data network

    Science.gov (United States)

    Rowse, William

    Private Satellite Network currently operates Business Television networks for Fortune 500 companies. Several of these satellite-based networks, using VSAT technology, are combining the transmission of video with the broadcast of one-way data. This is made possible by use of the PSN Business Television Terminal which incorporates Scientific Atlanta's B-MAC system. In addition to providing high quality video, B-MAC can provide six channels of 204.5 kbs audio. Four of the six channels may be used to directly carry up to 19.2 kbs of asynchronous data or up to 56 kbs of synchronous data using circuitry jointly developed by PSN and Scientific Atlanta. The approach PSN has taken to provide one network customer in the financial industry with both video and broadcast data is described herein.

  20. Adaptive generalized matrix projective lag synchronization between two different complex networks with non-identical nodes and different dimensions

    International Nuclear Information System (INIS)

    Dai Hao; Jia Li-Xin; Zhang Yan-Bin

    2012-01-01

    The adaptive generalized matrix projective lag synchronization between two different complex networks with non-identical nodes and different dimensions is investigated in this paper. Based on Lyapunov stability theory and Barbalat's lemma, generalized matrix projective lag synchronization criteria are derived by using the adaptive control method. Furthermore, each network can be undirected or directed, connected or disconnected, and nodes in either network may have identical or different dynamics. The proposed strategy is applicable to almost all kinds of complex networks. In addition, numerical simulation results are presented to illustrate the effectiveness of this method, showing that the synchronization speed is sensitively influenced by the adaptive law strength, the network size, and the network topological structure. (general)

  1. Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

    Science.gov (United States)

    Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

    2015-10-01

    This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Dynamic robustness of knowledge collaboration network of open source product development community

    Science.gov (United States)

    Zhou, Hong-Li; Zhang, Xiao-Dong

    2018-01-01

    As an emergent innovative design style, open source product development communities are characterized by a self-organizing, mass collaborative, networked structure. The robustness of the community is critical to its performance. Using the complex network modeling method, the knowledge collaboration network of the community is formulated, and the robustness of the network is systematically and dynamically studied. The characteristics of the network along the development period determine that its robustness should be studied from three time stages: the start-up, development and mature stages of the network. Five kinds of user-loss pattern are designed, to assess the network's robustness under different situations in each of these three time stages. Two indexes - the largest connected component and the network efficiency - are used to evaluate the robustness of the community. The proposed approach is applied in an existing open source car design community. The results indicate that the knowledge collaboration networks show different levels of robustness in different stages and different user loss patterns. Such analysis can be applied to provide protection strategies for the key users involved in knowledge dissemination and knowledge contribution at different stages of the network, thereby promoting the sustainable and stable development of the open source community.

  3. Distributed synchronization of networked drive-response systems: A nonlinear fixed-time protocol.

    Science.gov (United States)

    Zhao, Wen; Liu, Gang; Ma, Xi; He, Bing; Dong, Yunfeng

    2017-11-01

    The distributed synchronization of networked drive-response systems is investigated in this paper. A novel nonlinear protocol is proposed to ensure that the tracking errors converge to zeros in a fixed-time. By comparison with previous synchronization methods, the present method considers more practical conditions and the synchronization time is not dependent of arbitrary initial conditions but can be offline pre-assign according to the task assignment. Finally, the feasibility and validity of the presented protocol have been illustrated by a numerical simulation. Copyright © 2017. Published by Elsevier Ltd.

  4. Generalized synchronization between chimera states

    Science.gov (United States)

    Andrzejak, Ralph G.; Ruzzene, Giulia; Malvestio, Irene

    2017-05-01

    Networks of coupled oscillators in chimera states are characterized by an intriguing interplay of synchronous and asynchronous motion. While chimera states were initially discovered in mathematical model systems, there is growing experimental and conceptual evidence that they manifest themselves also in natural and man-made networks. In real-world systems, however, synchronization and desynchronization are not only important within individual networks but also across different interacting networks. It is therefore essential to investigate if chimera states can be synchronized across networks. To address this open problem, we use the classical setting of ring networks of non-locally coupled identical phase oscillators. We apply diffusive drive-response couplings between pairs of such networks that individually show chimera states when there is no coupling between them. The drive and response networks are either identical or they differ by a variable mismatch in their phase lag parameters. In both cases, already for weak couplings, the coherent domain of the response network aligns its position to the one of the driver networks. For identical networks, a sufficiently strong coupling leads to identical synchronization between the drive and response. For non-identical networks, we use the auxiliary system approach to demonstrate that generalized synchronization is established instead. In this case, the response network continues to show a chimera dynamics which however remains distinct from the one of the driver. Hence, segregated synchronized and desynchronized domains in individual networks congregate in generalized synchronization across networks.

  5. Effects of Coupling Distance on Synchronization and Coherence in Chaotic Neural Networks

    International Nuclear Information System (INIS)

    Wang Maosheng

    2009-01-01

    Effects of coupling distance on synchronization and coherence of chaotic neurons in complex networks are numerically investigated. We find that it is not beneficial to neurons synchronization if confining the coupling distance of random edges to a limit d max , but help to improve their coherence. Moreover, there is an optimal value of d max at which the coherence is maximum.

  6. An effective method to improve the robustness of small-world networks under attack

    International Nuclear Information System (INIS)

    Zhang Zheng-Zhen; Xu Wen-Jun; Lin Jia-Ru; Zeng Shang-You

    2014-01-01

    In this study, the robustness of small-world networks to three types of attack is investigated. Global efficiency is introduced as the network coefficient to measure the robustness of a small-world network. The simulation results prove that an increase in rewiring probability or average degree can enhance the robustness of the small-world network under all three types of attack. The effectiveness of simultaneously increasing both rewiring probability and average degree is also studied, and the combined increase is found to significantly improve the robustness of the small-world network. Furthermore, the combined effect of rewiring probability and average degree on network robustness is shown to be several times greater than that of rewiring probability or average degree individually. This means that small-world networks with a relatively high rewiring probability and average degree have advantages both in network communications and in good robustness to attacks. Therefore, simultaneously increasing rewiring probability and average degree is an effective method of constructing realistic networks. Consequently, the proposed method is useful to construct efficient and robust networks in a realistic scenario. (interdisciplinary physics and related areas of science and technology)

  7. Structural and robustness properties of smart-city transportation networks

    Science.gov (United States)

    Zhang, Zhen-Gang; Ding, Zhuo; Fan, Jing-Fang; Meng, Jun; Ding, Yi-Min; Ye, Fang-Fu; Chen, Xiao-Song

    2015-09-01

    The concept of smart city gives an excellent resolution to construct and develop modern cities, and also demands infrastructure construction. How to build a safe, stable, and highly efficient public transportation system becomes an important topic in the process of city construction. In this work, we study the structural and robustness properties of transportation networks and their sub-networks. We introduce a complementary network model to study the relevance and complementarity between bus network and subway network. Our numerical results show that the mutual supplement of networks can improve the network robustness. This conclusion provides a theoretical basis for the construction of public traffic networks, and it also supports reasonable operation of managing smart cities. Project supported by the Major Projects of the China National Social Science Fund (Grant No. 11 & ZD154).

  8. Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

    Science.gov (United States)

    Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

    In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

  9. Pinning synchronization of delayed complex dynamical networks with nonlinear coupling

    Science.gov (United States)

    Cheng, Ranran; Peng, Mingshu; Yu, Weibin

    2014-11-01

    In this paper, we find that complex networks with the Watts-Strogatz or scale-free BA random topological architecture can be synchronized more easily by pin-controlling fewer nodes than regular systems. Theoretical analysis is included by means of Lyapunov functions and linear matrix inequalities (LMI) to make all nodes reach complete synchronization. Numerical examples are also provided to illustrate the importance of our theoretical analysis, which implies that there exists a gap between the theoretical prediction and numerical results about the minimum number of pinning controlled nodes.

  10. GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

    Directory of Open Access Journals (Sweden)

    Meeri Eeva-Liisa Mäkinen

    2018-03-01

    Full Text Available The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging and temporal resolution microelectrode array (MEA. We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling.

  11. GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

    Science.gov (United States)

    Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

    2018-01-01

    The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893

  12. Satellite network robust QoS-aware routing

    CERN Document Server

    Long, Fei

    2014-01-01

    Satellite Network Robust QoS-aware Routing presents a novel routing strategy for satellite networks. This strategy is useful for the design of multi-layered satellite networks as it can greatly reduce the number of time slots in one system cycle. The traffic prediction and engineering approaches make the system robust so that the traffic spikes can be handled effectively. The multi-QoS optimization routing algorithm can satisfy various potential user requirements. Clear and sufficient illustrations are also presented in the book. As the chapters cover the above topics independently, readers from different research backgrounds in constellation design, multi-QoS routing, and traffic engineering can benefit from the book.   Fei Long is a senior engineer at Beijing R&D Center of 54th Research Institute of China Electronics Technology Group Corporation.

  13. Multiple types of synchronization analysis for discontinuous Cohen-Grossberg neural networks with time-varying delays.

    Science.gov (United States)

    Li, Jiarong; Jiang, Haijun; Hu, Cheng; Yu, Zhiyong

    2018-03-01

    This paper is devoted to the exponential synchronization, finite time synchronization, and fixed-time synchronization of Cohen-Grossberg neural networks (CGNNs) with discontinuous activations and time-varying delays. Discontinuous feedback controller and Novel adaptive feedback controller are designed to realize global exponential synchronization, finite time synchronization and fixed-time synchronization by adjusting the values of the parameters ω in the controller. Furthermore, the settling time of the fixed-time synchronization derived in this paper is less conservative and more accurate. Finally, some numerical examples are provided to show the effectiveness and flexibility of the results derived in this paper. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Quantifying Neural Oscillatory Synchronization: A Comparison between Spectral Coherence and Phase-Locking Value Approaches

    Science.gov (United States)

    Lowet, Eric; Roberts, Mark J.; Bonizzi, Pietro; Karel, Joël; De Weerd, Peter

    2016-01-01

    Synchronization or phase-locking between oscillating neuronal groups is considered to be important for coordination of information among cortical networks. Spectral coherence is a commonly used approach to quantify phase locking between neural signals. We systematically explored the validity of spectral coherence measures for quantifying synchronization among neural oscillators. To that aim, we simulated coupled oscillatory signals that exhibited synchronization dynamics using an abstract phase-oscillator model as well as interacting gamma-generating spiking neural networks. We found that, within a large parameter range, the spectral coherence measure deviated substantially from the expected phase-locking. Moreover, spectral coherence did not converge to the expected value with increasing signal-to-noise ratio. We found that spectral coherence particularly failed when oscillators were in the partially (intermittent) synchronized state, which we expect to be the most likely state for neural synchronization. The failure was due to the fast frequency and amplitude changes induced by synchronization forces. We then investigated whether spectral coherence reflected the information flow among networks measured by transfer entropy (TE) of spike trains. We found that spectral coherence failed to robustly reflect changes in synchrony-mediated information flow between neural networks in many instances. As an alternative approach we explored a phase-locking value (PLV) method based on the reconstruction of the instantaneous phase. As one approach for reconstructing instantaneous phase, we used the Hilbert Transform (HT) preceded by Singular Spectrum Decomposition (SSD) of the signal. PLV estimates have broad applicability as they do not rely on stationarity, and, unlike spectral coherence, they enable more accurate estimations of oscillatory synchronization across a wide range of different synchronization regimes, and better tracking of synchronization-mediated information

  15. Quantifying Neural Oscillatory Synchronization: A Comparison between Spectral Coherence and Phase-Locking Value Approaches.

    Directory of Open Access Journals (Sweden)

    Eric Lowet

    Full Text Available Synchronization or phase-locking between oscillating neuronal groups is considered to be important for coordination of information among cortical networks. Spectral coherence is a commonly used approach to quantify phase locking between neural signals. We systematically explored the validity of spectral coherence measures for quantifying synchronization among neural oscillators. To that aim, we simulated coupled oscillatory signals that exhibited synchronization dynamics using an abstract phase-oscillator model as well as interacting gamma-generating spiking neural networks. We found that, within a large parameter range, the spectral coherence measure deviated substantially from the expected phase-locking. Moreover, spectral coherence did not converge to the expected value with increasing signal-to-noise ratio. We found that spectral coherence particularly failed when oscillators were in the partially (intermittent synchronized state, which we expect to be the most likely state for neural synchronization. The failure was due to the fast frequency and amplitude changes induced by synchronization forces. We then investigated whether spectral coherence reflected the information flow among networks measured by transfer entropy (TE of spike trains. We found that spectral coherence failed to robustly reflect changes in synchrony-mediated information flow between neural networks in many instances. As an alternative approach we explored a phase-locking value (PLV method based on the reconstruction of the instantaneous phase. As one approach for reconstructing instantaneous phase, we used the Hilbert Transform (HT preceded by Singular Spectrum Decomposition (SSD of the signal. PLV estimates have broad applicability as they do not rely on stationarity, and, unlike spectral coherence, they enable more accurate estimations of oscillatory synchronization across a wide range of different synchronization regimes, and better tracking of synchronization

  16. Community structure in real-world networks from a non-parametrical synchronization-based dynamical approach

    International Nuclear Information System (INIS)

    Moujahid, Abdelmalik; D’Anjou, Alicia; Cases, Blanca

    2012-01-01

    Highlights: ► A synchronization-based algorithm for community structure detection is proposed. ► We model a complex network based on coupled nonidentical chaotic Rössler oscillators. ► The interaction scheme contemplates an uniformly increasing coupling force. ► The frequencies of oscillators are adapted according to a parameterless mechanism. ► The adaptation mechanism reveals the community structure present in the network. - Abstract: This work analyzes the problem of community structure in real-world networks based on the synchronization of nonidentical coupled chaotic Rössler oscillators each one characterized by a defined natural frequency, and coupled according to a predefined network topology. The interaction scheme contemplates an uniformly increasing coupling force to simulate a society in which the association between the agents grows in time. To enhance the stability of the correlated states that could emerge from the synchronization process, we propose a parameterless mechanism that adapts the characteristic frequencies of coupled oscillators according to a dynamic connectivity matrix deduced from correlated data. We show that the characteristic frequency vector that results from the adaptation mechanism reveals the underlying community structure present in the network.

  17. Pinning synchronization of the complex networks with non-delayed and delayed coupling

    International Nuclear Information System (INIS)

    Guo Wanli; Austin, Francis; Chen Shihua; Sun Wen

    2009-01-01

    In this Letter, without assuming the symmetry of the coupling matrix, we investigate the global synchronization of the complex networks with non-delayed and delayed coupling based on the pinning controllers. Some sufficient conditions for the global synchronization by adding linear and adaptive feedback controllers to a part of nodes are obtained. Numerical examples are also provided to demonstrate the effectiveness of the theory.

  18. Robust Adaptive Sliding Mode Control for Generalized Function Projective Synchronization of Different Chaotic Systems with Unknown Parameters

    Directory of Open Access Journals (Sweden)

    Xiuchun Li

    2013-01-01

    Full Text Available When the parameters of both drive and response systems are all unknown, an adaptive sliding mode controller, strongly robust to exotic perturbations, is designed for realizing generalized function projective synchronization. Sliding mode surface is given and the controlled system is asymptotically stable on this surface with the passage of time. Based on the adaptation laws and Lyapunov stability theory, an adaptive sliding controller is designed to ensure the occurrence of the sliding motion. Finally, numerical simulations are presented to verify the effectiveness and robustness of the proposed method even when both drive and response systems are perturbed with external disturbances.

  19. New conditions on synchronization of networks of linearly coupled dynamical systems with non-Lipschitz right-hand sides.

    Science.gov (United States)

    Liu, Bo; Lu, Wenlian; Chen, Tianping

    2012-01-01

    In this paper, we study synchronization of networks of linearly coupled dynamical systems. The node dynamics of the network can be very general, which may not satisfy the QUAD condition. We derive sufficient conditions for synchronization, which can be regarded as extensions of previous results. These results can be employed to networks of coupled systems, of which, in particular, the node dynamics have non-Lipschitz or even discontinuous right-hand sides. We also give several corollaries where the synchronization of some specific non-QUAD systems can be deduced. As an application, we propose a scheme to realize synchronization of coupled switching systems via coupling the signals which drive the switchings. Examples with numerical simulations are also provided to illustrate the theoretical results. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. Inferring topologies via driving-based generalized synchronization of two-layer networks

    Science.gov (United States)

    Wang, Yingfei; Wu, Xiaoqun; Feng, Hui; Lu, Jun-an; Xu, Yuhua

    2016-05-01

    The interaction topology among the constituents of a complex network plays a crucial role in the network’s evolutionary mechanisms and functional behaviors. However, some network topologies are usually unknown or uncertain. Meanwhile, coupling delays are ubiquitous in various man-made and natural networks. Hence, it is necessary to gain knowledge of the whole or partial topology of a complex dynamical network by taking into consideration communication delay. In this paper, topology identification of complex dynamical networks is investigated via generalized synchronization of a two-layer network. Particularly, based on the LaSalle-type invariance principle of stochastic differential delay equations, an adaptive control technique is proposed by constructing an auxiliary layer and designing proper control input and updating laws so that the unknown topology can be recovered upon successful generalized synchronization. Numerical simulations are provided to illustrate the effectiveness of the proposed method. The technique provides a certain theoretical basis for topology inference of complex networks. In particular, when the considered network is composed of systems with high-dimension or complicated dynamics, a simpler response layer can be constructed, which is conducive to circuit design. Moreover, it is practical to take into consideration perturbations caused by control input. Finally, the method is applicable to infer topology of a subnetwork embedded within a complex system and locate hidden sources. We hope the results can provide basic insight into further research endeavors on understanding practical and economical topology inference of networks.

  1. Synchronization from second order network connectivity statistics

    Directory of Open Access Journals (Sweden)

    Liqiong eZhao

    2011-07-01

    Full Text Available We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks (SONETs, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by a pool and redistribute mechanism. The pooling of many inputs averages out independent fluctuations, amplifying weak correlations in the inputs. With increased chain connections, neurons with many inputs tend to have many outputs. Hence, chains ensure that the amplified correlations in the neurons with many inputs are redistributed throughout the network, enhancing the development of synchrony across the network.

  2. Event-based cluster synchronization of coupled genetic regulatory networks

    Science.gov (United States)

    Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang

    2017-09-01

    In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

  3. BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

    Science.gov (United States)

    Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

    2015-06-12

    During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

  4. Robust synchronization of drive-response chaotic systems via adaptive sliding mode control

    International Nuclear Information System (INIS)

    Li, W.-L.; Chang, K.-M.

    2009-01-01

    A robust adaptive sliding control scheme is developed in this study to achieve synchronization for two identical chaotic systems in the presence of uncertain system parameters, external disturbances and nonlinear control inputs. An adaptation algorithm is given based on the Lyapunov stability theory. Using this adaptation technique to estimate the upper-bounds of parameter variation and external disturbance uncertainties, an adaptive sliding mode controller is then constructed without requiring the bounds of parameter and disturbance uncertainties to be known in advance. It is proven that the proposed adaptive sliding mode controller can maintain the existence of sliding mode in finite time in uncertain chaotic systems. Finally, numerical simulations are presented to show the effectiveness of the proposed control scheme.

  5. Global robust stability of delayed recurrent neural networks

    International Nuclear Information System (INIS)

    Cao Jinde; Huang Deshuang; Qu Yuzhong

    2005-01-01

    This paper is concerned with the global robust stability of a class of delayed interval recurrent neural networks which contain time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. A new sufficient condition is presented for the existence, uniqueness, and global robust stability of equilibria for interval neural networks with time delays by constructing Lyapunov functional and using matrix-norm inequality. An error is corrected in an earlier publication, and an example is given to show the effectiveness of the obtained results

  6. Robustness of the p53 network and biological hackers.

    Science.gov (United States)

    Dartnell, Lewis; Simeonidis, Evangelos; Hubank, Michael; Tsoka, Sophia; Bogle, I David L; Papageorgiou, Lazaros G

    2005-06-06

    The p53 protein interaction network is crucial in regulating the metazoan cell cycle and apoptosis. Here, the robustness of the p53 network is studied by analyzing its degeneration under two modes of attack. Linear Programming is used to calculate average path lengths among proteins and the network diameter as measures of functionality. The p53 network is found to be robust to random loss of nodes, but vulnerable to a targeted attack against its hubs, as a result of its architecture. The significance of the results is considered with respect to mutational knockouts of proteins and the directed attacks mounted by tumour inducing viruses.

  7. Robust visual tracking via multiscale deep sparse networks

    Science.gov (United States)

    Wang, Xin; Hou, Zhiqiang; Yu, Wangsheng; Xue, Yang; Jin, Zefenfen; Dai, Bo

    2017-04-01

    In visual tracking, deep learning with offline pretraining can extract more intrinsic and robust features. It has significant success solving the tracking drift in a complicated environment. However, offline pretraining requires numerous auxiliary training datasets and is considerably time-consuming for tracking tasks. To solve these problems, a multiscale sparse networks-based tracker (MSNT) under the particle filter framework is proposed. Based on the stacked sparse autoencoders and rectifier linear unit, the tracker has a flexible and adjustable architecture without the offline pretraining process and exploits the robust and powerful features effectively only through online training of limited labeled data. Meanwhile, the tracker builds four deep sparse networks of different scales, according to the target's profile type. During tracking, the tracker selects the matched tracking network adaptively in accordance with the initial target's profile type. It preserves the inherent structural information more efficiently than the single-scale networks. Additionally, a corresponding update strategy is proposed to improve the robustness of the tracker. Extensive experimental results on a large scale benchmark dataset show that the proposed method performs favorably against state-of-the-art methods in challenging environments.

  8. Exponential stabilization and synchronization for fuzzy model of memristive neural networks by periodically intermittent control.

    Science.gov (United States)

    Yang, Shiju; Li, Chuandong; Huang, Tingwen

    2016-03-01

    The problem of exponential stabilization and synchronization for fuzzy model of memristive neural networks (MNNs) is investigated by using periodically intermittent control in this paper. Based on the knowledge of memristor and recurrent neural network, the model of MNNs is formulated. Some novel and useful stabilization criteria and synchronization conditions are then derived by using the Lyapunov functional and differential inequality techniques. It is worth noting that the methods used in this paper are also applied to fuzzy model for complex networks and general neural networks. Numerical simulations are also provided to verify the effectiveness of theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Peng; QI Wen-Juan; DENG Zi-Li

    2014-01-01

    This paper investigates the distributed fusion Kalman filtering over clustering sensor networks. The sensor network is partitioned as clusters by the nearest neighbor rule and each cluster consists of sensing nodes and cluster-head. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, two-level robust measurement fusion Kalman filter is presented for the clustering sensor network systems with uncertain noise variances. It can significantly reduce the communication load and save energy when the number of sensors is very large. A Lyapunov equation approach for the robustness analysis is presented, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented, and the robust accuracy relations among the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the two-level weighted measurement fuser is equal to that of the global centralized robust fuser and is higher than those of each local robust filter and each local weighted measurement fuser. A simulation example shows the correctness and effectiveness of the proposed results.

  10. Exponential synchronization of two nonlinearly non-delayed and delayed coupled complex dynamical networks

    International Nuclear Information System (INIS)

    Zheng Song

    2012-01-01

    In this paper, the exponential synchronization between two nonlinearly coupled complex networks with non-delayed and delayed coupling is investigated with Lyapunov-Krasovskii-type functionals. Based on the stability analysis of the impulsive differential equation and the linear matrix inequality, sufficient delay-dependent conditions for exponential synchronization are derived, and a linear impulsive controller and simple updated laws are also designed. Furthermore, the coupling matrices need not be symmetric or irreducible. Numerical examples are presented to verify the effectiveness and correctness of the synchronization criteria obtained.

  11. Global synchronization in arrays of delayed neural networks with constant and delayed coupling

    International Nuclear Information System (INIS)

    Cao Jinde; Li Ping; Wang Weiwei

    2006-01-01

    This Letter investigates the global exponential synchronization in arrays of coupled identical delayed neural networks (DNNs) with constant and delayed coupling. By referring to Lyapunov functional method and Kronecker product technique, some sufficient conditions are derived for global synchronization of such systems. These new synchronization criteria offer some adjustable matrix parameters, which is of important significance in the design and applications of such coupled DNNs, and the results improve and extend the earlier works. Finally, an example is given to illustrate the theoretical results

  12. A Gossip-based Energy Efficient Protocol for Robust In-network Aggregation in Wireless Sensor Networks

    Science.gov (United States)

    Fauji, Shantanu

    We consider the problem of energy efficient and fault tolerant in--network aggregation for wireless sensor networks (WSNs). In-network aggregation is the process of aggregation while collecting data from sensors to the base station. This process should be energy efficient due to the limited energy at the sensors and tolerant to the high failure rates common in sensor networks. Tree based in--network aggregation protocols, although energy efficient, are not robust to network failures. Multipath routing protocols are robust to failures to a certain degree but are not energy efficient due to the overhead in the maintenance of multiple paths. We propose a new protocol for in-network aggregation in WSNs, which is energy efficient, achieves high lifetime, and is robust to the changes in the network topology. Our protocol, gossip--based protocol for in-network aggregation (GPIA) is based on the spreading of information via gossip. GPIA is not only adaptive to failures and changes in the network topology, but is also energy efficient. Energy efficiency of GPIA comes from all the nodes being capable of selective message reception and detecting convergence of the aggregation early. We experimentally show that GPIA provides significant improvement over some other competitors like the Ridesharing, Synopsis Diffusion and the pure version of gossip. GPIA shows ten fold, five fold and two fold improvement over the pure gossip, the synopsis diffusion and Ridesharing protocols in terms of network lifetime, respectively. Further, GPIA retains gossip's robustness to failures and improves upon the accuracy of synopsis diffusion and Ridesharing.

  13. Impact of Loss Synchronization on Reliable High Speed Networks: A Model Based Simulation

    Directory of Open Access Journals (Sweden)

    Suman Kumar

    2014-01-01

    Full Text Available Contemporary nature of network evolution demands for simulation models which are flexible, scalable, and easily implementable. In this paper, we propose a fluid based model for performance analysis of reliable high speed networks. In particular, this paper aims to study the dynamic relationship between congestion control algorithms and queue management schemes, in order to develop a better understanding of the causal linkages between the two. We propose a loss synchronization module which is user configurable. We validate our model through simulations under controlled settings. Also, we present a performance analysis to provide insights into two important issues concerning 10 Gbps high speed networks: (i impact of bottleneck buffer size on the performance of 10 Gbps high speed network and (ii impact of level of loss synchronization on link utilization-fairness tradeoffs. The practical impact of the proposed work is to provide design guidelines along with a powerful simulation tool to protocol designers and network developers.

  14. Novel results for global robust stability of delayed neural networks

    International Nuclear Information System (INIS)

    Yucel, Eylem; Arik, Sabri

    2009-01-01

    This paper investigates the global robust convergence properties of continuous-time neural networks with discrete time delays. By employing suitable Lyapunov functionals, some sufficient conditions for the existence, uniqueness and global robust asymptotic stability of the equilibrium point are derived. The conditions can be easily verified as they can be expressed in terms of the network parameters only. Some numerical examples are also given to compare our results with previous robust stability results derived in the literature.

  15. Finite-Time Synchronizing Control for Chaotic Neural Networks

    Directory of Open Access Journals (Sweden)

    Chao Zhang

    2014-01-01

    Full Text Available This paper addresses the finite-time synchronizing problem for a class of chaotic neural networks. In a real communication network, parameters of the master system may be time-varying and the system may be perturbed by external disturbances. A simple high-gain observer is designed to track all the nonlinearities, unknown system functions, and disturbances. Then, a dynamic active compensatory controller is proposed and by using the singular perturbation theory, the control method can guarantee the finite-time stability of the error system between the master system and the slave system. Finally, two illustrative examples are provided to show the effectiveness and applicability of the proposed scheme.

  16. Mirror node correlations tuning synchronization in multiplex networks

    Science.gov (United States)

    Kumar, Anil; Baptista, Murilo S.; Zaikin, Alexey; Jalan, Sarika

    2017-12-01

    We show that the degree-degree correlations have a major impact on global synchronizability (GS) of multiplex networks, enabling the specification of synchronizability by only changing the degree-degree correlations of the mirror nodes while maintaining the connection architecture of the individual layer unaltered. If individual layers have nodes that are mildly correlated, the multiplex network is best synchronizable when the mirror degrees are strongly negatively correlated. If individual layers have nodes with strong degree-degree correlations, mild correlations among the degrees of mirror nodes are the best strategy for the optimization of GS. Global synchronization also depend on the density of connections, a phenomenon not observed in a single layer network. The results are crucial to understand, predict, and specify behavior of systems having multiple types of connections among the interacting units.

  17. Robustness leads close to the edge of chaos in coupled map networks: toward the understanding of biological networks

    International Nuclear Information System (INIS)

    Saito, Nen; Kikuchi, Macoto

    2013-01-01

    Dynamics in biological networks are, in general, robust against several perturbations. We investigate a coupled map network as a model motivated by gene regulatory networks and design systems that are robust against phenotypic perturbations (perturbations in dynamics), as well as systems that are robust against mutation (perturbations in network structure). To achieve such a design, we apply a multicanonical Monte Carlo method. Analysis based on the maximum Lyapunov exponent and parameter sensitivity shows that systems with marginal stability, which are regarded as systems at the edge of chaos, emerge when robustness against network perturbations is required. This emergence of the edge of chaos is a self-organization phenomenon and does not need a fine tuning of parameters. (paper)

  18. Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

    Science.gov (United States)

    Chen, Tien-Chi; Yu, Chih-Hsien

    2009-07-01

    A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

  19. Exponential cluster synchronization in directed community networks via adaptive nonperiodically intermittent pinning control

    Science.gov (United States)

    Zhou, Peipei; Cai, Shuiming; Jiang, Shengqin; Liu, Zengrong

    2018-02-01

    In this paper, the problem of exponential cluster synchronization for a class of directed community networks is investigated via adaptive nonperiodically intermittent pinning control. By constructing a novel piecewise continuous Lyapunov function, some sufficient conditions to guarantee globally exponential cluster synchronization are derived. It is noted that the derived cluster synchronization criteria rely on the control rates, but not the control widths or the control periods, which facilitates the choice of the control periods in practical applications. A numerical example is finally presented to show the effectiveness of the obtained theoretical results.

  20. Synchronization in scale-free networks: The role of finite-size effects

    Science.gov (United States)

    Torres, D.; Di Muro, M. A.; La Rocca, C. E.; Braunstein, L. A.

    2015-06-01

    Synchronization problems in complex networks are very often studied by researchers due to their many applications to various fields such as neurobiology, e-commerce and completion of tasks. In particular, scale-free networks with degree distribution P(k)∼ k-λ , are widely used in research since they are ubiquitous in Nature and other real systems. In this paper we focus on the surface relaxation growth model in scale-free networks with 2.5< λ <3 , and study the scaling behavior of the fluctuations, in the steady state, with the system size N. We find a novel behavior of the fluctuations characterized by a crossover between two regimes at a value of N=N* that depends on λ: a logarithmic regime, found in previous research, and a constant regime. We propose a function that describes this crossover, which is in very good agreement with the simulations. We also find that, for a system size above N* , the fluctuations decrease with λ, which means that the synchronization of the system improves as λ increases. We explain this crossover analyzing the role of the network's heterogeneity produced by the system size N and the exponent of the degree distribution.

  1. International business cycle synchronization since the 1870s: Evidence from a novel network approach

    Science.gov (United States)

    Antonakakis, Nikolaos; Gogas, Periklis; Papadimitriou, Theophilos; Sarantitis, Georgios Antonios

    2016-04-01

    In this study, we examine the issue of business cycle synchronization from a historical perspective in 27 developed and developing countries. Based on a novel complex network approach, the Threshold-Minimum Dominating Set (T-MDS), our results reveal heterogeneous patterns of international business cycle synchronization during fundamental globalization periods since the 1870s. In particular, the proposed methodology reveals that worldwide business cycles de-coupled during the Gold Standard, though they were synchronized during the Great Depression. The Bretton Woods era was associated with a lower degree of synchronization as compared to that during the Great Depression, while worldwide business cycle synchronization increased to unprecedented levels during the latest period of floating exchange rates and the Great Recession.

  2. Reconfigurable Robust Routing for Mobile Outreach Network

    Science.gov (United States)

    Lin, Ching-Fang

    2010-01-01

    The Reconfigurable Robust Routing for Mobile Outreach Network (R3MOO N) provides advanced communications networking technologies suitable for the lunar surface environment and applications. The R3MOON techn ology is based on a detailed concept of operations tailored for luna r surface networks, and includes intelligent routing algorithms and wireless mesh network implementation on AGNC's Coremicro Robots. The product's features include an integrated communication solution inco rporating energy efficiency and disruption-tolerance in a mobile ad h oc network, and a real-time control module to provide researchers an d engineers a convenient tool for reconfiguration, investigation, an d management.

  3. A delay fractioning approach to global synchronization of delayed complex networks with stochastic disturbances

    International Nuclear Information System (INIS)

    Wang Yao; Wang Zidong; Liang Jinling

    2008-01-01

    In this Letter, the synchronization problem is investigated for a class of stochastic complex networks with time delays. By utilizing a new Lyapunov functional form based on the idea of 'delay fractioning', we employ the stochastic analysis techniques and the properties of Kronecker product to establish delay-dependent synchronization criteria that guarantee the globally asymptotically mean-square synchronization of the addressed delayed networks with stochastic disturbances. These sufficient conditions, which are formulated in terms of linear matrix inequalities (LMIs), can be solved efficiently by the LMI toolbox in Matlab. The main results are proved to be much less conservative and the conservatism could be reduced further as the number of delay fractioning gets bigger. A simulation example is exploited to demonstrate the advantage and applicability of the proposed result

  4. Synchronization Algorithm for SDN-controlled All-Optical TDM Switching in a Random Length Ring Network

    DEFF Research Database (Denmark)

    Kamchevska, Valerija; Cristofori, Valentina; Da Ros, Francesco

    2016-01-01

    We propose and demonstrate an algorithm that allows for automatic synchronization of SDN-controlled all-optical TDM switching nodes connected in a ring network. We experimentally show successful WDM-SDM transmission of data bursts between all ring nodes.......We propose and demonstrate an algorithm that allows for automatic synchronization of SDN-controlled all-optical TDM switching nodes connected in a ring network. We experimentally show successful WDM-SDM transmission of data bursts between all ring nodes....

  5. Robust classification using mixtures of dependency networks

    DEFF Research Database (Denmark)

    Gámez, José A.; Mateo, Juan L.; Nielsen, Thomas Dyhre

    2008-01-01

    Dependency networks have previously been proposed as alternatives to e.g. Bayesian networks by supporting fast algorithms for automatic learning. Recently dependency networks have also been proposed as classification models, but as with e.g. general probabilistic inference, the reported speed......-ups are often obtained at the expense of accuracy. In this paper we try to address this issue through the use of mixtures of dependency networks. To reduce learning time and improve robustness when dealing with data sparse classes, we outline methods for reusing calculations across mixture components. Finally...

  6. Robust Synchronization Models for Presentation System Using SMIL-Driven Approach

    Science.gov (United States)

    Asnawi, Rustam; Ahmad, Wan Fatimah Wan; Rambli, Dayang Rohaya Awang

    2013-01-01

    Current common Presentation System (PS) models are slide based oriented and lack synchronization analysis either with temporal or spatial constraints. Such models, in fact, tend to lead to synchronization problems, particularly on parallel synchronization with spatial constraints between multimedia element presentations. However, parallel…

  7. Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events.

    Science.gov (United States)

    Zhou, Yaoming; Sheu, Jiuh-Biing; Wang, Junwei

    2017-08-01

    Robustness measures a system's ability of being insensitive to disturbances. Previous studies assessed the robustness of transportation networks to a single disturbance without considering simultaneously happening multiple events. The purpose of this article is to address this problem and propose a new framework to assess the robustness of an urban transportation network. The framework consists of two layers. The upper layer is to define the robustness index based on the impact evaluation in different scenarios obtained from the lower layer, whereas the lower layer is to evaluate the performance of each hypothetical disrupted road network given by the upper layer. The upper layer has two varieties, that is, robustness against random failure and robustness against intentional attacks. This robustness measurement framework is validated by application to a real-world urban road network in Hong Kong. The results show that the robustness of a transport network with consideration of multiple events is quite different from and more comprehensive than that with consideration of only a single disruption. We also propose a Monte Carlo method and a heuristic algorithm to handle different scenarios with multiple hazard events, which is proved to be quite efficient. This methodology can also be applied to conduct risk analysis of other systems where multiple failures or disruptions exist. © 2017 Society for Risk Analysis.

  8. Characterization of complex networks : Application to robustness analysis

    NARCIS (Netherlands)

    Jamakovic, A.

    2008-01-01

    This thesis focuses on the topological characterization of complex networks. It specifically focuses on those elementary graph measures that are of interest when quantifying topology-related aspects of the robustness of complex networks. This thesis makes the following contributions to the field of

  9. A Group Neighborhood Average Clock Synchronization Protocol for Wireless Sensor Networks

    Science.gov (United States)

    Lin, Lin; Ma, Shiwei; Ma, Maode

    2014-01-01

    Clock synchronization is a very important issue for the applications of wireless sensor networks. The sensors need to keep a strict clock so that users can know exactly what happens in the monitoring area at the same time. This paper proposes a novel internal distributed clock synchronization solution using group neighborhood average. Each sensor node collects the offset and skew rate of the neighbors. Group averaging of offset and skew rate value are calculated instead of conventional point-to-point averaging method. The sensor node then returns compensated value back to the neighbors. The propagation delay is considered and compensated. The analytical analysis of offset and skew compensation is presented. Simulation results validate the effectiveness of the protocol and reveal that the protocol allows sensor networks to quickly establish a consensus clock and maintain a small deviation from the consensus clock. PMID:25120163

  10. Time signal distribution in communication networks based on synchronous digital hierarchy

    Science.gov (United States)

    Imaoka, Atsushi; Kihara, Masami

    1993-01-01

    A new method that uses round-trip paths to accurately measure transmission delay for time synchronization is proposed. The performance of the method in Synchronous Digital Hierarchy networks is discussed. The feature of this method is that it separately measures the initial round trip path delay and the variations in round-trip path delay. The delay generated in SDH equipment is determined by measuring the initial round-trip path delay. In an experiment with actual SDH equipment, the error of initial delay measurement was suppressed to 30ns.

  11. Pinning synchronization of two general complex networks with periodically intermittent control

    Directory of Open Access Journals (Sweden)

    Meng Fanyu

    2015-12-01

    Full Text Available In this paper, the method of periodically pinning intermittent control is introduced to solve the problem of outer synchronization between two complex networks. Based on the Lyapunov stability theory, differential inequality method and adaptive technique, some simple synchronous criteria have been derived analytically. At last, both the theoretical and numerical analysis illustrate the effectiveness of the proposed control methodology. This method not only reduces the conservatism of control gain but also saves the cost of production.These advantages make this method having a large application scope in the real production process.

  12. SYNCHRONIZATION OF NATIONAL GRID NETWORK WITH THE ELECTRICITY SHIPS NETWORK IN THE "SHORE TO SHIP" SYSTEM

    Directory of Open Access Journals (Sweden)

    Dariusz TARNAPOWICZ

    2013-07-01

    Full Text Available ‘Shore to ship’ system – ships’ power supply from the local electrical substations – is one of the effective ways to limit the negative impact of the ships lying in ports on the environment. Energy infrastructure of the port installation necessary to provide ships with power supply has to be designed so that different types of ships can use it. The important issue concerning ‘shore to ship’ system is the quality of power supply. This can be achieved via sustaining continuity of power supply while switching from the ships’ electrical network over to the national grid. In this article the author presents the way of synchronizing the national grid with the ships’ electrical network during ship’s lying in port. Such synchronization would allow for uninterruptible work of the ship’s electrical devices.

  13. Robust Frame Synchronization for Low Signal-to-Noise Ratio Channels Using Energy-Corrected Differential Correlation

    Directory of Open Access Journals (Sweden)

    Kim Pansoo

    2009-01-01

    Full Text Available Recent standards for wireless transmission require reliable synchronization for channels with low signal-to-noise ratio (SNR as well as with a large amount of frequency offset, which necessitates a robust correlator structure for the initial frame synchronization process. In this paper, a new correlation strategy especially targeted for low SNR regions is proposed and its performance is analyzed. By utilizing a modified energy correction term, the proposed method effectively reduces the variance of the decision variable to enhance the detection performance. Most importantly, the method is demonstrated to outperform all previously reported schemes by a significant margin, for SNRs below 5 dB regardless of the existence of the frequency offsets. A variation of the proposed method is also presented for further enhancement over the channels with small frequency errors. The particular application considered for the performance verification is the second generation digital video broadcasting system for satellites (DVB-S2.

  14. On the Interplay between Entropy and Robustness of Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Bor-Sen Chen

    2010-05-01

    Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

  15. Optimisation in the Design of Environmental Sensor Networks with Robustness Consideration

    Science.gov (United States)

    Budi, Setia; de Souza, Paulo; Timms, Greg; Malhotra, Vishv; Turner, Paul

    2015-01-01

    This work proposes the design of Environmental Sensor Networks (ESN) through balancing robustness and redundancy. An Evolutionary Algorithm (EA) is employed to find the optimal placement of sensor nodes in the Region of Interest (RoI). Data quality issues are introduced to simulate their impact on the performance of the ESN. Spatial Regression Test (SRT) is also utilised to promote robustness in data quality of the designed ESN. The proposed method provides high network representativeness (fit for purpose) with minimum sensor redundancy (cost), and ensures robustness by enabling the network to continue to achieve its objectives when some sensors fail. PMID:26633392

  16. Robustness of Dengue Complex Network under Targeted versus Random Attack

    Directory of Open Access Journals (Sweden)

    Hafiz Abid Mahmood Malik

    2017-01-01

    Full Text Available Dengue virus infection is one of those epidemic diseases that require much consideration in order to save the humankind from its unsafe impacts. According to the World Health Organization (WHO, 3.6 billion individuals are at risk because of the dengue virus sickness. Researchers are striving to comprehend the dengue threat. This study is a little commitment to those endeavors. To observe the robustness of the dengue network, we uprooted the links between nodes randomly and targeted by utilizing different centrality measures. The outcomes demonstrated that 5% targeted attack is equivalent to the result of 65% random assault, which showed the topology of this complex network validated a scale-free network instead of random network. Four centrality measures (Degree, Closeness, Betweenness, and Eigenvector have been ascertained to look for focal hubs. It has been observed through the results in this study that robustness of a node and links depends on topology of the network. The dengue epidemic network presented robust behaviour under random attack, and this network turned out to be more vulnerable when the hubs of higher degree have higher probability to fail. Moreover, representation of this network has been projected, and hub removal impact has been shown on the real map of Gombak (Malaysia.

  17. Attacks on the Network Synchronization Systems Counteraction Method Implemented in the Software and Hardware Device «MARSH! 3.0»

    Directory of Open Access Journals (Sweden)

    Dmitry Anatolevich Melnikov

    2013-12-01

    Full Text Available This paper proposes attacks on the network synchronization systems counteraction technique, method, algorithm and realizable aspects. The network synchronization systems are included in information technology systems or networks. This method is implemented in software and hardware device (means «MARSH! 3.0» providing trusted session.

  18. Exponential synchronization of complex delayed dynamical networks via pinning periodically intermittent control

    Energy Technology Data Exchange (ETDEWEB)

    Cai Shuiming, E-mail: caishuiming2008@yahoo.com.c [Department of Mathematics, Shanghai University, Shanghai 200444 (China); Institute of System Biology, Shanghai University, Shanghai 200444 (China); Hao Junjun [Institute of System Biology, Shanghai University, Shanghai 200444 (China); He, Qinbin [Department of Mathematics, Taizhou University, Linhai 317000 (China); Institute of System Biology, Shanghai University, Shanghai 200444 (China); Liu Zengrong, E-mail: zrongliu@126.co [Department of Mathematics, Shanghai University, Shanghai 200444 (China) and Institute of System Biology, Shanghai University, Shanghai 200444 (China)

    2011-05-09

    The problem of synchronization for a class of complex delayed dynamical networks via pinning periodically intermittent control is considered in this Letter. Some novel and useful exponential synchronization criteria are obtained by utilizing the methods which are different from the techniques employed in the existing works, and the derived results are less conservative. Especially, the traditional assumptions on control width and time delays are released in our results. Moreover, a pinning scheme deciding what nodes should be chosen as pinned candidates and how many nodes are needed to be pinned for a fixed coupling strength is provided. A Barabasi-Albert network example is finally given to illustrate the effectiveness of the theoretical results. - Highlights: Pinning control problem of complex networks via intermittent control is investigated. The traditional assumptions on control width and time delays are removed. A scheme deciding what nodes should be chosen as pinned candidates is proposed. A scheme deciding how many nodes are needed to be pinned is provided.

  19. Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates

    Directory of Open Access Journals (Sweden)

    Chih-Hong Kao

    2011-01-01

    Full Text Available This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme.

  20. Finite-time hybrid projective synchronization of the drive-response complex networks with distributed-delay via adaptive intermittent control

    Science.gov (United States)

    Cheng, Lin; Yang, Yongqing; Li, Li; Sui, Xin

    2018-06-01

    This paper studies the finite-time hybrid projective synchronization of the drive-response complex networks. In the model, general transmission delays and distributed delays are also considered. By designing the adaptive intermittent controllers, the response network can achieve hybrid projective synchronization with the drive system in finite time. Based on finite-time stability theory and several differential inequalities, some simple finite-time hybrid projective synchronization criteria are derived. Two numerical examples are given to illustrate the effectiveness of the proposed method.

  1. Ordering chaos and synchronization transitions by chemical delay and coupling on scale-free neuronal networks

    International Nuclear Information System (INIS)

    Gong Yubing; Xie Yanhang; Lin Xiu; Hao Yinghang; Ma Xiaoguang

    2010-01-01

    Research highlights: → Chemical delay and chemical coupling can tame chaotic bursting. → Chemical delay-induced transitions from bursting synchronization to intermittent multiple spiking synchronizations. → Chemical coupling-induced different types of delay-dependent firing transitions. - Abstract: Chemical synaptic connections are more common than electric ones in neurons, and information transmission delay is especially significant for the synapses of chemical type. In this paper, we report a phenomenon of ordering spatiotemporal chaos and synchronization transitions by the delays and coupling through chemical synapses of modified Hodgkin-Huxley (MHH) neurons on scale-free networks. As the delay τ is increased, the neurons exhibit transitions from bursting synchronization (BS) to intermittent multiple spiking synchronizations (SS). As the coupling g syn is increased, the neurons exhibit different types of firing transitions, depending on the values of τ. For a smaller τ, there are transitions from spatiotemporal chaotic bursting (SCB) to BS or SS; while for a larger τ, there are transitions from SCB to intermittent multiple SS. These findings show that the delays and coupling through chemical synapses can tame the chaotic firings and repeatedly enhance the firing synchronization of neurons, and hence could play important roles in the firing activity of the neurons on scale-free networks.

  2. Research on robust optimization of emergency logistics network considering the time dependence characteristic

    Science.gov (United States)

    WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

    2017-06-01

    Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

  3. Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks.

    Science.gov (United States)

    Hu, Cheng; Yu, Juan; Chen, Zhanheng; Jiang, Haijun; Huang, Tingwen

    2017-05-01

    In this paper, the fixed-time stability of dynamical systems and the fixed-time synchronization of coupled discontinuous neural networks are investigated under the framework of Filippov solution. Firstly, by means of reduction to absurdity, a theorem of fixed-time stability is established and a high-precision estimation of the settling-time is given. It is shown by theoretic proof that the estimation bound of the settling time given in this paper is less conservative and more accurate compared with the classical results. Besides, as an important application, the fixed-time synchronization of coupled neural networks with discontinuous activation functions is proposed. By designing a discontinuous control law and using the theory of differential inclusions, some new criteria are derived to ensure the fixed-time synchronization of the addressed coupled networks. Finally, two numerical examples are provided to show the effectiveness and validity of the theoretical results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Global exponential synchronization of inertial memristive neural networks with time-varying delay via nonlinear controller.

    Science.gov (United States)

    Gong, Shuqing; Yang, Shaofu; Guo, Zhenyuan; Huang, Tingwen

    2018-06-01

    The paper is concerned with the synchronization problem of inertial memristive neural networks with time-varying delay. First, by choosing a proper variable substitution, inertial memristive neural networks described by second-order differential equations can be transformed into first-order differential equations. Then, a novel controller with a linear diffusive term and discontinuous sign term is designed. By using the controller, the sufficient conditions for assuring the global exponential synchronization of the derive and response neural networks are derived based on Lyapunov stability theory and some inequality techniques. Finally, several numerical simulations are provided to substantiate the effectiveness of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance.

    Science.gov (United States)

    Siebenhühner, Felix; Wang, Sheng H; Palva, J Matias; Palva, Satu

    2016-09-26

    Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha-gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions.

  6. Mechanisms of zero-lag synchronization in cortical motifs.

    Directory of Open Access Journals (Sweden)

    Leonardo L Gollo

    2014-04-01

    Full Text Available Zero-lag synchronization between distant cortical areas has been observed in a diversity of experimental data sets and between many different regions of the brain. Several computational mechanisms have been proposed to account for such isochronous synchronization in the presence of long conduction delays: Of these, the phenomenon of "dynamical relaying"--a mechanism that relies on a specific network motif--has proven to be the most robust with respect to parameter mismatch and system noise. Surprisingly, despite a contrary belief in the community, the common driving motif is an unreliable means of establishing zero-lag synchrony. Although dynamical relaying has been validated in empirical and computational studies, the deeper dynamical mechanisms and comparison to dynamics on other motifs is lacking. By systematically comparing synchronization on a variety of small motifs, we establish that the presence of a single reciprocally connected pair--a "resonance pair"--plays a crucial role in disambiguating those motifs that foster zero-lag synchrony in the presence of conduction delays (such as dynamical relaying from those that do not (such as the common driving triad. Remarkably, minor structural changes to the common driving motif that incorporate a reciprocal pair recover robust zero-lag synchrony. The findings are observed in computational models of spiking neurons, populations of spiking neurons and neural mass models, and arise whether the oscillatory systems are periodic, chaotic, noise-free or driven by stochastic inputs. The influence of the resonance pair is also robust to parameter mismatch and asymmetrical time delays amongst the elements of the motif. We call this manner of facilitating zero-lag synchrony resonance-induced synchronization, outline the conditions for its occurrence, and propose that it may be a general mechanism to promote zero-lag synchrony in the brain.

  7. Complex interdependent supply chain networks: Cascading failure and robustness

    Science.gov (United States)

    Tang, Liang; Jing, Ke; He, Jie; Stanley, H. Eugene

    2016-02-01

    A supply chain network is a typical interdependent network composed of an undirected cyber-layer network and a directed physical-layer network. To analyze the robustness of this complex interdependent supply chain network when it suffers from disruption events that can cause nodes to fail, we use a cascading failure process that focuses on load propagation. We consider load propagation via connectivity links as node failure spreads through one layer of an interdependent network, and we develop a priority redistribution strategy for failed loads subject to flow constraint. Using a giant component function and a one-to-one directed interdependence relation between nodes in a cyber-layer network and physical-layer network, we construct time-varied functional equations to quantify the dynamic process of failed loads propagation in an interdependent network. Finally, we conduct a numerical simulation for two cases, i.e., single node removal and multiple node removal at the initial disruption. The simulation results show that when we increase the number of removed nodes in an interdependent supply chain network its robustness undergoes a first-order discontinuous phase transition, and that even removing a small number of nodes will cause it to crash.

  8. Effects of traffic generation patterns on the robustness of complex networks

    Science.gov (United States)

    Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui

    2018-02-01

    Cascading failures in communication networks with heterogeneous node functions are studied in this paper. In such networks, the traffic dynamics are highly dependent on the traffic generation patterns which are in turn determined by the locations of the hosts. The data-packet traffic model is applied to Barabási-Albert scale-free networks to study the cascading failures in such networks and to explore the effects of traffic generation patterns on network robustness. It is found that placing the hosts at high-degree nodes in a network can make the network more robust against both intentional attacks and random failures. It is also shown that the traffic generation pattern plays an important role in network design.

  9. A decentralized scheduling algorithm for time synchronized channel hopping

    Directory of Open Access Journals (Sweden)

    Andrew Tinka

    2011-09-01

    Full Text Available Time Synchronized Channel Hopping (TSCH is an existing Medium Access Control scheme which enables robust communication through channel hopping and high data rates through synchronization. It is based on a time-slotted architecture, and its correct functioning depends on a schedule which is typically computed by a central node. This paper presents, to our knowledge, the first scheduling algorithm for TSCH networks which both is distributed and which copes with mobile nodes. Two variations on scheduling algorithms are presented. Aloha-based scheduling allocates one channel for broadcasting advertisements for new neighbors. Reservation- based scheduling augments Aloha-based scheduling with a dedicated timeslot for targeted advertisements based on gossip information. A mobile ad hoc motorized sensor network with frequent connectivity changes is studied, and the performance of the two proposed algorithms is assessed. This performance analysis uses both simulation results and the results of a field deployment of floating wireless sensors in an estuarial canal environment. Reservation-based scheduling performs significantly better than Aloha-based scheduling, suggesting that the improved network reactivity is worth the increased algorithmic complexity and resource consumption.

  10. A Group Neighborhood Average Clock Synchronization Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Lin Lin

    2014-08-01

    Full Text Available Clock synchronization is a very important issue for the applications of wireless sensor networks. The sensors need to keep a strict clock so that users can know exactly what happens in the monitoring area at the same time. This paper proposes a novel internal distributed clock synchronization solution using group neighborhood average. Each sensor node collects the offset and skew rate of the neighbors. Group averaging of offset and skew rate value are calculated instead of conventional point-to-point averaging method. The sensor node then returns compensated value back to the neighbors. The propagation delay is considered and compensated. The analytical analysis of offset and skew compensation is presented. Simulation results validate the effectiveness of the protocol and reveal that the protocol allows sensor networks to quickly establish a consensus clock and maintain a small deviation from the consensus clock.

  11. Robust Synchronization of Fractional-Order Chaotic Systems at a Pre-Specified Time Using Sliding Mode Controller with Time-Varying Switching Surfaces

    International Nuclear Information System (INIS)

    Khanzadeh, Alireza; Pourgholi, Mahdi

    2016-01-01

    A main problem associated with the synchronization of two chaotic systems is that the time in which complete synchronization will occur is not specified. Synchronization time is either infinitely large or is finite but only its upper bound is known and this bound depends on the systems' initial conditions. In this paper we propose a method for synchronizing of two chaotic systems precisely at a time which we want. To this end, time-varying switching surfaces sliding mode control is used and the control law based on Lyapunov stability theorem is derived which is able to synchronize two fractional-order chaotic systems precisely at a pre specified time without concerning about their initial conditions. Moreover, by eliminating the reaching phase in the proposed synchronization scheme, robustness against existence of uncertainties and exogenous disturbances is obtained. Because of the existence of fractional integral of the sign function instead of the sign function in the control equation, the necessity for infinitely fast switching be obviated in this method. To show the effectiveness of the proposed method the illustrative examples under different situations are provided and the simulation results are reported.

  12. Developing a robust wireless sensor network structure for environmental sensing

    Science.gov (United States)

    Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

    2013-12-01

    The American River Hydrologic Observatory is being strategically deployed as a real-time ground-based measurement network that delivers accurate and timely information on snow conditions and other hydrologic attributes with a previously unheard of granularity of time and space. The basin-scale network involves 18 sub-networks set out at physiographically representative locations spanning the seasonally snow-covered half of the 5000 km2 American river basin. Each sub-network, covering about a 1-km2 area, consists of 10 wirelessly networked sensing nodes that continuously measure and telemeter temperature, and snow depth; plus selected locations are equipped with sensors for relative humidity, solar radiation, and soil moisture at several depths. The sensor locations were chosen to maximize the variance sampled for snow depth within the basin. Network design and deployment involves an iterative but efficient process. After sensor-station locations are determined, a robust network of interlinking sensor stations and signal repeaters must be constructed to route sensor data to a central base station with a two-way communicable data uplink. Data can then be uploaded from site to remote servers in real time through satellite and cell modems. Signal repeaters are placed for robustness of a self-healing network with redundant signal paths to the base station. Manual, trial-and-error heuristic approaches for node placement are inefficient and labor intensive. In that approach field personnel must restructure the network in real time and wait for new network statistics to be calculated at the base station before finalizing a placement, acting without knowledge of the global topography or overall network structure. We show how digital elevation plus high-definition aerial photographs to give foliage coverage can optimize planning of signal repeater placements and guarantee a robust network structure prior to the physical deployment. We can also 'stress test' the final network

  13. How the self-coupled neuron can affect the chaotic synchronization of network

    International Nuclear Information System (INIS)

    Jia Chenhui; Wang Jiang; Deng, Bin

    2009-01-01

    We have calculated 34 kinds of three-cell neuron networks' minimum coupling strength, from the result; we find that a self-coupled neuron can have some effect on the synchronization of the network. The reason is the self-coupled neurons make the number of neurons looks 'decrease', and they decrease the coupling strength of the other neurons which are coupled with them.

  14. Fixed-time synchronization of complex networks with nonidentical nodes and stochastic noise perturbations

    Science.gov (United States)

    Zhang, Wanli; Li, Chuandong; Huang, Tingwen; Huang, Junjian

    2018-02-01

    This paper investigates the fixed-time synchronization of complex networks (CNs) with nonidentical nodes and stochastic noise perturbations. By designing new controllers, constructing Lyapunov functions and using the properties of Weiner process, different synchronization criteria are derived according to whether the node systems in the CNs or the goal system satisfies the corresponding conditions. Moreover, the role of the designed controllers is analyzed in great detail by constructing a suitable comparison system and a new method is presented to estimate the settling time by utilizing the comparison system. Results of this paper can be applied to both directed and undirected weighted networks. Numerical simulations are offered to verify the effectiveness of our new results.

  15. ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

    KAUST Repository

    Kuwahara, Hiroyuki; Umarov, Ramzan; Almasri, Islam; Gao, Xin

    2017-01-01

    To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

  16. ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

    KAUST Repository

    Kuwahara, Hiroyuki

    2017-03-01

    To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

  17. Combined effect of chemical and electrical synapses in Hindmarsh-Rose neural networks on synchronization and the rate of information.

    Science.gov (United States)

    Baptista, M S; Moukam Kakmeni, F M; Grebogi, C

    2010-09-01

    In this work we studied the combined action of chemical and electrical synapses in small networks of Hindmarsh-Rose (HR) neurons on the synchronous behavior and on the rate of information produced (per time unit) by the networks. We show that if the chemical synapse is excitatory, the larger the chemical synapse strength used the smaller the electrical synapse strength needed to achieve complete synchronization, and for moderate synaptic strengths one should expect to find desynchronous behavior. Otherwise, if the chemical synapse is inhibitory, the larger the chemical synapse strength used the larger the electrical synapse strength needed to achieve complete synchronization, and for moderate synaptic strengths one should expect to find synchronous behaviors. Finally, we show how to calculate semianalytically an upper bound for the rate of information produced per time unit (Kolmogorov-Sinai entropy) in larger networks. As an application, we show that this upper bound is linearly proportional to the number of neurons in a network whose neurons are highly connected.

  18. Dynamic Control of Synchronous Activity in Networks of Spiking Neurons.

    Directory of Open Access Journals (Sweden)

    Axel Hutt

    Full Text Available Oscillatory brain activity is believed to play a central role in neural coding. Accumulating evidence shows that features of these oscillations are highly dynamic: power, frequency and phase fluctuate alongside changes in behavior and task demands. The role and mechanism supporting this variability is however poorly understood. We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. We show that afferent noise, mimicking inputs to the neurons, causes smoothing of the system's response function, displacing equilibria and altering the stability of oscillatory states. Our analysis further shows that these noise-induced changes cause a shift of the peak frequency of synchronous oscillations that scales with input intensity, leading the network towards critical states. We lastly discuss the extension of these principles to periodic stimulation, in which externally applied driving signals can trigger analogous phenomena. Our results reveal one possible mechanism involved in shaping oscillatory activity in the brain and associated control principles.

  19. Dynamic Control of Synchronous Activity in Networks of Spiking Neurons.

    Science.gov (United States)

    Hutt, Axel; Mierau, Andreas; Lefebvre, Jérémie

    Oscillatory brain activity is believed to play a central role in neural coding. Accumulating evidence shows that features of these oscillations are highly dynamic: power, frequency and phase fluctuate alongside changes in behavior and task demands. The role and mechanism supporting this variability is however poorly understood. We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. We show that afferent noise, mimicking inputs to the neurons, causes smoothing of the system's response function, displacing equilibria and altering the stability of oscillatory states. Our analysis further shows that these noise-induced changes cause a shift of the peak frequency of synchronous oscillations that scales with input intensity, leading the network towards critical states. We lastly discuss the extension of these principles to periodic stimulation, in which externally applied driving signals can trigger analogous phenomena. Our results reveal one possible mechanism involved in shaping oscillatory activity in the brain and associated control principles.

  20. High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention.

    Science.gov (United States)

    Lobier, Muriel; Palva, J Matias; Palva, Satu

    2018-01-15

    Visuospatial attention prioritizes processing of attended visual stimuli. It is characterized by lateralized alpha-band (8-14 Hz) amplitude suppression in visual cortex and increased neuronal activity in a network of frontal and parietal areas. It has remained unknown what mechanisms coordinate neuronal processing among frontoparietal network and visual cortices and implement the attention-related modulations of alpha-band amplitudes and behavior. We investigated whether large-scale network synchronization could be such a mechanism. We recorded human cortical activity with magnetoencephalography (MEG) during a visuospatial attention task. We then identified the frequencies and anatomical networks of inter-areal phase synchronization from source localized MEG data. We found that visuospatial attention is associated with robust and sustained long-range synchronization of cortical oscillations exclusively in the high-alpha (10-14 Hz) frequency band. This synchronization connected frontal, parietal and visual regions and was observed concurrently with amplitude suppression of low-alpha (6-9 Hz) band oscillations in visual cortex. Furthermore, stronger high-alpha phase synchronization was associated with decreased reaction times to attended stimuli and larger suppression of alpha-band amplitudes. These results thus show that high-alpha band phase synchronization is functionally significant and could coordinate the neuronal communication underlying the implementation of visuospatial attention. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Robust network design for multispecies conservation

    Science.gov (United States)

    Ronan Le Bras; Bistra Dilkina; Yexiang Xue; Carla P. Gomes; Kevin S. McKelvey; Michael K. Schwartz; Claire A. Montgomery

    2013-01-01

    Our work is motivated by an important network design application in computational sustainability concerning wildlife conservation. In the face of human development and climate change, it is important that conservation plans for protecting landscape connectivity exhibit certain level of robustness. While previous work has focused on conservation strategies that result...

  2. Partial synchronization of different chaotic oscillators using robust PID feedback

    Energy Technology Data Exchange (ETDEWEB)

    Aguilar-Lopez, Ricardo [Departamento de Energia, Universidad Autonoma Metropolitana - Azcapotzalco, San Pablo 180, Reynosa-Tamaulipas, Azcapotzalco, 02200 Mexico, D.F. (Mexico)]. E-mail: raguilar@correo.azc.uam.mx; Martinez-Guerra, Rafael [Departamento de Control Automatico, CINVESTAV IPN, Apartado Postal 14-740, Mexico, D.F. C.P. 07360 (Mexico)]. E-mail: rguerra@ctrl.cinvestav.mx

    2007-07-15

    This work deals with the partial synchronization problem of two different chaotic oscillators considering model uncertainties in the slave system via control approach. The slave system is forced to follow the master signal via a linearizing controller based on model uncertainty reconstructor which leads to proportional-integral-derivative (PID) control structure. This reconstructor is related with a proportional-derivative (PD) reduced-order observer, it would be considered as a sub-slave system for the original slave of the synchronization procedure. The asymptotic performance of the synchronization methodology is proven via the dynamic of the synchronization error. Numerical experiment illustrates the closed-loop behavior of the proposed methodology.

  3. Partial synchronization of different chaotic oscillators using robust PID feedback

    International Nuclear Information System (INIS)

    Aguilar-Lopez, Ricardo; Martinez-Guerra, Rafael

    2007-01-01

    This work deals with the partial synchronization problem of two different chaotic oscillators considering model uncertainties in the slave system via control approach. The slave system is forced to follow the master signal via a linearizing controller based on model uncertainty reconstructor which leads to proportional-integral-derivative (PID) control structure. This reconstructor is related with a proportional-derivative (PD) reduced-order observer, it would be considered as a sub-slave system for the original slave of the synchronization procedure. The asymptotic performance of the synchronization methodology is proven via the dynamic of the synchronization error. Numerical experiment illustrates the closed-loop behavior of the proposed methodology

  4. Robustness of assembly supply chain networks by considering risk propagation and cascading failure

    Science.gov (United States)

    Tang, Liang; Jing, Ke; He, Jie; Stanley, H. Eugene

    2016-10-01

    An assembly supply chain network (ASCN) is composed of manufacturers located in different geographical regions. To analyze the robustness of this ASCN when it suffers from catastrophe disruption events, we construct a cascading failure model of risk propagation. In our model, different disruption scenarios s are considered and the probability equation of all disruption scenarios is developed. Using production capability loss as the robustness index (RI) of an ASCN, we conduct a numerical simulation to assess its robustness. Through simulation, we compare the network robustness at different values of linking intensity and node threshold and find that weak linking intensity or high node threshold increases the robustness of the ASCN. We also compare network robustness levels under different disruption scenarios.

  5. Robust chaos synchronization using input-to-state stable control

    Indian Academy of Sciences (India)

    In this paper, we propose a new input-to-state stable (ISS) synchronization method for a general class of chaotic systems with disturbances. Based on Lyapunov theory and linear matrix inequality (LMI) approach, for the first time, the ISS synchronization controller is presented not only to guarantee the asymptotic ...

  6. Pinning Synchronization of Delayed Neural Networks with Nonlinear Inner-Coupling

    Directory of Open Access Journals (Sweden)

    Yangling Wang

    2011-01-01

    Full Text Available Without assuming the symmetry and irreducibility of the outer-coupling weight configuration matrices, we investigate the pinning synchronization of delayed neural networks with nonlinear inner-coupling. Some delay-dependent controlled stability criteria in terms of linear matrix inequality (LMI are obtained. An example is presented to show the application of the criteria obtained in this paper.

  7. Economic networks: Heterogeneity-induced vulnerability and loss of synchronization

    Science.gov (United States)

    Colon, Célian; Ghil, Michael

    2017-12-01

    Interconnected systems are prone to propagation of disturbances, which can undermine their resilience to external perturbations. Propagation dynamics can clearly be affected by potential time delays in the underlying processes. We investigate how such delays influence the resilience of production networks facing disruption of supply. Interdependencies between economic agents are modeled using systems of Boolean delay equations (BDEs); doing so allows us to introduce heterogeneity in production delays and in inventories. Complex network topologies are considered that reproduce realistic economic features, including a network of networks. Perturbations that would otherwise vanish can, because of delay heterogeneity, amplify and lead to permanent disruptions. This phenomenon is enabled by the interactions between short cyclic structures. Difference in delays between two interacting, and otherwise resilient, structures can in turn lead to loss of synchronization in damage propagation and thus prevent recovery. Finally, this study also shows that BDEs on complex networks can lead to metastable relaxation oscillations, which are damped out in one part of a network while moving on to another part.

  8. Some new results on stability and synchronization for delayed inertial neural networks based on non-reduced order method.

    Science.gov (United States)

    Li, Xuanying; Li, Xiaotong; Hu, Cheng

    2017-12-01

    In this paper, without transforming the second order inertial neural networks into the first order differential systems by some variable substitutions, asymptotic stability and synchronization for a class of delayed inertial neural networks are investigated. Firstly, a new Lyapunov functional is constructed to directly propose the asymptotic stability of the inertial neural networks, and some new stability criteria are derived by means of Barbalat Lemma. Additionally, by designing a new feedback control strategy, the asymptotic synchronization of the addressed inertial networks is studied and some effective conditions are obtained. To reduce the control cost, an adaptive control scheme is designed to realize the asymptotic synchronization. It is noted that the dynamical behaviors of inertial neural networks are directly analyzed in this paper by constructing some new Lyapunov functionals, this is totally different from the traditional reduced-order variable substitution method. Finally, some numerical simulations are given to demonstrate the effectiveness of the derived theoretical results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Climate network analysis of regional precipitation extremes: The true story told by event synchronization

    Science.gov (United States)

    Odenweller, Adrian; Donner, Reik V.

    2017-04-01

    Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two

  10. Partial synchronization in networks of non-linearly coupled oscillators: The Deserter Hubs Model

    Energy Technology Data Exchange (ETDEWEB)

    Freitas, Celso, E-mail: cbnfreitas@gmail.com; Macau, Elbert, E-mail: elbert.macau@inpe.br [Associate Laboratory for Computing and Applied Mathematics - LAC, Brazilian National Institute for Space Research - INPE (Brazil); Pikovsky, Arkady, E-mail: pikovsky@uni-potsdam.de [Department of Physics and Astronomy, University of Potsdam, Germany and Department of Control Theory, Nizhni Novgorod State University, Gagarin Av. 23, 606950, Nizhni Novgorod (Russian Federation)

    2015-04-15

    We study the Deserter Hubs Model: a Kuramoto-like model of coupled identical phase oscillators on a network, where attractive and repulsive couplings are balanced dynamically due to nonlinearity of interactions. Under weak force, an oscillator tends to follow the phase of its neighbors, but if an oscillator is compelled to follow its peers by a sufficient large number of cohesive neighbors, then it actually starts to act in the opposite manner, i.e., in anti-phase with the majority. Analytic results yield that if the repulsion parameter is small enough in comparison with the degree of the maximum hub, then the full synchronization state is locally stable. Numerical experiments are performed to explore the model beyond this threshold, where the overall cohesion is lost. We report in detail partially synchronous dynamical regimes, like stationary phase-locking, multistability, periodic and chaotic states. Via statistical analysis of different network organizations like tree, scale-free, and random ones, we found a measure allowing one to predict relative abundance of partially synchronous stationary states in comparison to time-dependent ones.

  11. Partial Synchronization Manifolds for Linearly Time-Delay Coupled Systems

    OpenAIRE

    Steur, Erik; van Leeuwen, Cees; Michiels, Wim

    2014-01-01

    Sometimes a network of dynamical systems shows a form of incomplete synchronization characterized by synchronization of some but not all of its systems. This type of incomplete synchronization is called partial synchronization. Partial synchronization is associated with the existence of partial synchronization manifolds, which are linear invariant subspaces of C, the state space of the network of systems. We focus on partial synchronization manifolds in networks of system...

  12. A study of epileptogenic network structures in rat hippocampal cultures using first spike latencies during synchronization events

    International Nuclear Information System (INIS)

    Raghavan, Mohan; Amrutur, Bharadwaj; Srinivas, Kalyan V; Sikdar, Sujit K

    2012-01-01

    Study of hypersynchronous activity is of prime importance for combating epilepsy. Studies on network structure typically reconstruct the network by measuring various aspects of the interaction between neurons and subsequently measure the properties of the reconstructed network. In sub-sampled networks such methods lead to significant errors in reconstruction. Using rat hippocampal neurons cultured on a multi-electrode array dish and a glutamate injury model of epilepsy in vitro, we studied synchronous activity in neuronal networks. Using the first spike latencies in various neurons during a network burst, we extract various recurring spatio-temporal onset patterns in the networks. Comparing the patterns seen in control and injured networks, we observe that injured networks express a wide diversity in their foci (origin) and activation pattern, while control networks show limited diversity. Furthermore, we note that onset patterns in glutamate injured networks show a positive correlation between synchronization delay and physical distance between neurons, while control networks do not. (paper)

  13. The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

    International Nuclear Information System (INIS)

    Guo, Chunxiang; Liu, Xiaoli; Jin, Maozhu; Lv, Zhihan

    2016-01-01

    Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.

  14. Robust Learning of Fixed-Structure Bayesian Networks

    OpenAIRE

    Diakonikolas, Ilias; Kane, Daniel; Stewart, Alistair

    2016-01-01

    We investigate the problem of learning Bayesian networks in an agnostic model where an $\\epsilon$-fraction of the samples are adversarially corrupted. Our agnostic learning model is similar to -- in fact, stronger than -- Huber's contamination model in robust statistics. In this work, we study the fully observable Bernoulli case where the structure of the network is given. Even in this basic setting, previous learning algorithms either run in exponential time or lose dimension-dependent facto...

  15. Mixed H ∞ and Passive Projective Synchronization for Fractional Order Memristor-Based Neural Networks with Time-Delay and Parameter Uncertainty

    Science.gov (United States)

    Song, Xiao-Na; Song, Shuai; Tejado Balsera, Inés; Liu, Lei-Po

    2017-10-01

    This paper investigates the mixed H ∞ and passive projective synchronization problem for fractional-order (FO) memristor-based neural networks. Our aim is to design a controller such that, though the unavoidable phenomena of time-delay and parameter uncertainty are fully considered, the resulting closed-loop system is asymptotically stable with a mixed H ∞ and passive performance level. By combining active and adaptive control methods, a novel hybrid control strategy is designed, which can guarantee the robust stability of the closed-loop system and also ensure a mixed H ∞ and passive performance level. Via the application of FO Lyapunov stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequality techniques. Finally, two simulation examples are given to illustrate the effectiveness of the proposed method. Supported by National Natural Science Foundation of China under Grant Nos. U1604146, U1404610, 61473115, 61203047, Science and Technology Research Project in Henan Province under Grant Nos. 152102210273, 162102410024, and Foundation for the University Technological Innovative Talents of Henan Province under Grant No. 18HASTIT019

  16. Ramp time synchronization. [for NASA Deep Space Network

    Science.gov (United States)

    Hietzke, W.

    1979-01-01

    A new method of intercontinental clock synchronization has been developed and proposed for possible use by NASA's Deep Space Network (DSN), using a two-way/three-way radio link with a spacecraft. Analysis of preliminary data indicates that the real-time method has an uncertainty of 0.6 microsec, and it is very likely that further work will decrease the uncertainty. Also, the method is compatible with a variety of nonreal-time analysis techniques, which may reduce the uncertainty down to the tens of nanosecond range.

  17. Modeling stochasticity and robustness in gene regulatory networks.

    Science.gov (United States)

    Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

    2009-06-15

    Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

  18. Synchronization of an Inertial Neural Network With Time-Varying Delays and Its Application to Secure Communication.

    Science.gov (United States)

    Lakshmanan, Shanmugam; Prakash, Mani; Lim, Chee Peng; Rakkiyappan, Rajan; Balasubramaniam, Pagavathigounder; Nahavandi, Saeid

    2018-01-01

    In this paper, synchronization of an inertial neural network with time-varying delays is investigated. Based on the variable transformation method, we transform the second-order differential equations into the first-order differential equations. Then, using suitable Lyapunov-Krasovskii functionals and Jensen's inequality, the synchronization criteria are established in terms of linear matrix inequalities. Moreover, a feedback controller is designed to attain synchronization between the master and slave models, and to ensure that the error model is globally asymptotically stable. Numerical examples and simulations are presented to indicate the effectiveness of the proposed method. Besides that, an image encryption algorithm is proposed based on the piecewise linear chaotic map and the chaotic inertial neural network. The chaotic signals obtained from the inertial neural network are utilized for the encryption process. Statistical analyses are provided to evaluate the effectiveness of the proposed encryption algorithm. The results ascertain that the proposed encryption algorithm is efficient and reliable for secure communication applications.

  19. An Evaluation of optional timing/synchronization features to support selection of an optimum design for the DCS digital communication network

    Science.gov (United States)

    Bradley, D. B.; Cain, J. B., III; Williard, M. W.

    1978-01-01

    The task was to evaluate the ability of a set of timing/synchronization subsystem features to provide a set of desirable characteristics for the evolving Defense Communications System digital communications network. The set of features related to the approaches by which timing/synchronization information could be disseminated throughout the network and the manner in which this information could be utilized to provide a synchronized network. These features, which could be utilized in a large number of different combinations, included mutual control, directed control, double ended reference links, independence of clock error measurement and correction, phase reference combining, and self organizing.

  20. Fixed-time synchronization of memristor-based BAM neural networks with time-varying discrete delay.

    Science.gov (United States)

    Chen, Chuan; Li, Lixiang; Peng, Haipeng; Yang, Yixian

    2017-12-01

    This paper is devoted to studying the fixed-time synchronization of memristor-based BAM neural networks (MBAMNNs) with discrete delay. Fixed-time synchronization means that synchronization can be achieved in a fixed time for any initial values of the considered systems. In the light of the double-layer structure of MBAMNNs, we design two similar feedback controllers. Based on Lyapunov stability theories, several criteria are established to guarantee that the drive and response MBAMNNs can realize synchronization in a fixed time. In particular, by changing the parameters of controllers, this fixed time can be adjusted to some desired value in advance, irrespective of the initial values of MBAMNNs. Numerical simulations are included to validate the derived results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Fixed-Time Outer Synchronization of Complex Networks with Noise Coupling

    Science.gov (United States)

    Shi, Hong-Jun; Miao, Lian-Ying; Sun, Yong-Zheng; Liu, Mao-Xing

    2018-03-01

    In this paper, the fixed-time outer synchronization of complex networks with noise coupling is investigated. Based on the theory of fixed-time stability and matrix inequalities, sufficient conditions for fixed-time outer synchronization are established and the estimation of the upper bound of the setting time is obtained. The result shows that the setting time can be adjusted to a desired value regardless of the initial states. Numerical simulations are performed to verify the effectiveness of the theoretical results. The effects of control parameters and the density of controlled nodes on the converging time are studied. Supported by the National Natural Science Foundation of China under Grant Nos. 11711530203 and 11771443, and the Fundamental Research Funds for the Central Universities under Grant No. 2015XKMS076

  2. Random field Ising chain and neutral networks with synchronous dynamics

    International Nuclear Information System (INIS)

    Skantzos, N.S.; Coolen, A.C.C.

    2001-01-01

    We first present an exact solution of the one-dimensional random-field Ising model in which spin-updates are made fully synchronously, i.e. in parallel (in contrast to the more conventional Glauber-type sequential rules). We find transitions where the support of local observables turns from a continuous interval into a Cantor set and we show that synchronous and sequential random-field models lead asymptotically to the same physical states. We then proceed to an application of these techniques to recurrent neural networks where 1D short-range interactions are combined with infinite-range ones. Due to the competing interactions these models exhibit phase diagrams with first-order transitions and regions with multiple locally stable solutions for the macroscopic order parameters

  3. Design of the robust synchronous generator stator voltage regulator based on the interval plant model

    Directory of Open Access Journals (Sweden)

    Stojić Đorđe

    2013-01-01

    Full Text Available In this paper a novel method for the stator voltage regulator of a synchronous generator based on the interval plant mode, is presented. Namely, it is shown in the literature that, in order to design a controller for the first-order compensator, the limited number of interval plants needs to be examined. Consequently, the intervals of the plant model parameter variations used to calculate the four extreme interval plants required for the sequential PI controller design are determined. The controller is designed using frequency-domain-based techniques, while its robust performance is examined using simulation tests.

  4. Shape, size, and robustness: feasible regions in the parameter space of biochemical networks.

    Directory of Open Access Journals (Sweden)

    Adel Dayarian

    2009-01-01

    Full Text Available The concept of robustness of regulatory networks has received much attention in the last decade. One measure of robustness has been associated with the volume of the feasible region, namely, the region in the parameter space in which the system is functional. In this paper, we show that, in addition to volume, the geometry of this region has important consequences for the robustness and the fragility of a network. We develop an approximation within which we could algebraically specify the feasible region. We analyze the segment polarity gene network to illustrate our approach. The study of random walks in the parameter space and how they exit the feasible region provide us with a rich perspective on the different modes of failure of this network model. In particular, we found that, between two alternative ways of activating Wingless, one is more robust than the other. Our method provides a more complete measure of robustness to parameter variation. As a general modeling strategy, our approach is an interesting alternative to Boolean representation of biochemical networks.

  5. Distributed Synchronization in Communication Networks

    Science.gov (United States)

    2018-01-24

    synchronization. Secondly, it is known that identical oscillators with sin() coupling functions are guaranteed to synchronize in phase on a complete...provide sufficient conditions for phase- locking , i.e., convergence to a stable equilibrium almost surely. We additionally find conditions when the

  6. Phase synchronization in train connection timetables

    Energy Technology Data Exchange (ETDEWEB)

    Fretter, Christoph; Mueller-Hannemann, Matthias [Martin Luther Universitaet, Halle-Wittenberg (Germany); Krumov, Lachezar; Weihe, Karsten [TU Darmstadt (Germany); Huett, Marc-Thorsten [Jacobs University, Bremen (Germany)

    2010-07-01

    Train connection timetables are an important research topic in algorithmics. Finding optimal or near-optimal timetables under the subsidiary conditions of minimizing travel times and other criteria is an important contribution to the functioning of public transportation. In addition to efficiency (given, e.g. by minimal average travel times), the robustness of the timetable, i.e. a minimization of delay propagation, is an important criterion. Here we study the balance of efficiency and robustness in train connection timetables from the perspective of synchronization, exploiting the fact that a major part of the trains run nearly periodically. We find that synchronization is highest at intermediate-sized stations. We argue that this synchronization perspectives opens a new avenue towards an understanding of train connection timetables by representing them as spatiotemporal phase patterns. Robustness and efficiency can then be viewed as properties of this phase pattern.

  7. Robustness in Regulatory Interaction Networks. A Generic Approach with Applications at Different Levels: Physiologic, Metabolic and Genetic

    Science.gov (United States)

    Demongeot, Jacques; Ben Amor, Hedi; Elena, Adrien; Gillois, Pierre; Noual, Mathilde; Sené, Sylvain

    2009-01-01

    Regulatory interaction networks are often studied on their dynamical side (existence of attractors, study of their stability). We focus here also on their robustness, that is their ability to offer the same spatiotemporal patterns and to resist to external perturbations such as losses of nodes or edges in the networks interactions architecture, changes in their environmental boundary conditions as well as changes in the update schedule (or updating mode) of the states of their elements (e.g., if these elements are genes, their synchronous coexpression mode versus their sequential expression). We define the generic notions of boundary, core, and critical vertex or edge of the underlying interaction graph of the regulatory network, whose disappearance causes dramatic changes in the number and nature of attractors (e.g., passage from a bistable behaviour to a unique periodic regime) or in the range of their basins of stability. The dynamic transition of states will be presented in the framework of threshold Boolean automata rules. A panorama of applications at different levels will be given: brain and plant morphogenesis, bulbar cardio-respiratory regulation, glycolytic/oxidative metabolic coupling, and eventually cell cycle and feather morphogenesis genetic control. PMID:20057955

  8. Robustness in Regulatory Interaction Networks. A Generic Approach with Applications at Different Levels: Physiologic, Metabolic and Genetic

    Directory of Open Access Journals (Sweden)

    Sylvain Sené

    2009-10-01

    Full Text Available Regulatory interaction networks are often studied on their dynamical side (existence of attractors, study of their stability. We focus here also on their robustness, that is their ability to offer the same spatiotemporal patterns and to resist to external perturbations such as losses of nodes or edges in the networks interactions architecture, changes in their environmental boundary conditions as well as changes in the update schedule (or updating mode of the states of their elements (e.g., if these elements are genes, their synchronous coexpression mode versus their sequential expression. We define the generic notions of boundary, core, and critical vertex or edge of the underlying interaction graph of the regulatory network, whose disappearance causes dramatic changes in the number and nature of attractors (e.g., passage from a bistable behaviour to a unique periodic regime or in the range of their basins of stability. The dynamic transition of states will be presented in the framework of threshold Boolean automata rules. A panorama of applications at different levels will be given: brain and plant morphogenesis, bulbar cardio-respiratory regulation, glycolytic/oxidative metabolic coupling, and eventually cell cycle and feather morphogenesis genetic control.

  9. Introduction to focus issue: Synchronization in large networks and continuous media—data, models, and supermodels

    Science.gov (United States)

    Duane, Gregory S.; Grabow, Carsten; Selten, Frank; Ghil, Michael

    2017-12-01

    The synchronization of loosely coupled chaotic systems has increasingly found applications to large networks of differential equations and to models of continuous media. These applications are at the core of the present Focus Issue. Synchronization between a system and its model, based on limited observations, gives a new perspective on data assimilation. Synchronization among different models of the same system defines a supermodel that can achieve partial consensus among models that otherwise disagree in several respects. Finally, novel methods of time series analysis permit a better description of synchronization in a system that is only observed partially and for a relatively short time. This Focus Issue discusses synchronization in extended systems or in components thereof, with particular attention to data assimilation, supermodeling, and their applications to various areas, from climate modeling to macroeconomics.

  10. Introduction to focus issue: Synchronization in large networks and continuous media-data, models, and supermodels.

    Science.gov (United States)

    Duane, Gregory S; Grabow, Carsten; Selten, Frank; Ghil, Michael

    2017-12-01

    The synchronization of loosely coupled chaotic systems has increasingly found applications to large networks of differential equations and to models of continuous media. These applications are at the core of the present Focus Issue. Synchronization between a system and its model, based on limited observations, gives a new perspective on data assimilation. Synchronization among different models of the same system defines a supermodel that can achieve partial consensus among models that otherwise disagree in several respects. Finally, novel methods of time series analysis permit a better description of synchronization in a system that is only observed partially and for a relatively short time. This Focus Issue discusses synchronization in extended systems or in components thereof, with particular attention to data assimilation, supermodeling, and their applications to various areas, from climate modeling to macroeconomics.

  11. An Overview of a Class of Clock Synchronization Algorithms for Wireless Sensor Networks: A Statistical Signal Processing Perspective

    Directory of Open Access Journals (Sweden)

    Xu Wang

    2015-08-01

    Full Text Available Recently, wireless sensor networks (WSNs have drawn great interest due to their outstanding monitoring and management potential in medical, environmental and industrial applications. Most of the applications that employ WSNs demand all of the sensor nodes to run on a common time scale, a requirement that highlights the importance of clock synchronization. The clock synchronization problem in WSNs is inherently related to parameter estimation. The accuracy of clock synchronization algorithms depends essentially on the statistical properties of the parameter estimation algorithms. Recently, studies dedicated to the estimation of synchronization parameters, such as clock offset and skew, have begun to emerge in the literature. The aim of this article is to provide an overview of the state-of-the-art clock synchronization algorithms for WSNs from a statistical signal processing point of view. This article focuses on describing the key features of the class of clock synchronization algorithms that exploit the traditional two-way message (signal exchange mechanism. Upon introducing the two-way message exchange mechanism, the main clock offset estimation algorithms for pairwise synchronization of sensor nodes are first reviewed, and their performance is compared. The class of fully-distributed clock offset estimation algorithms for network-wide synchronization is then surveyed. The paper concludes with a list of open research problems pertaining to clock synchronization of WSNs.

  12. Synchronization and Control of Halo-Chaos in Beam Transport Network with Small World Topology

    International Nuclear Information System (INIS)

    Liu Qiang; Fang Jinqing; Li Yong

    2007-01-01

    The synchronous conditions of two kinds of the small-world (SW) network are studied. The small world topology can affect on dynamical behaviors of the beam transport network (BTN) largely, if the BTN is constructed with the SW topology, the global linear coupling and special linear feedback can realize the synchronization control of beam halo-chaos as well as periodic state in the BTN with the SW topology, respectively. This important result can provide an effective way for the experimental study and the engineering design of the BTN in the high-current accelerator driven radioactive clean nuclear power systems, and may have potential use in prospective applications for halo-chaos secure communication.

  13. Cascade-robustness optimization of coupling preference in interconnected networks

    International Nuclear Information System (INIS)

    Zhang, Xue-Jun; Xu, Guo-Qiang; Zhu, Yan-Bo; Xia, Yong-Xiang

    2016-01-01

    Highlights: • A specific memetic algorithm was proposed to optimize coupling links. • A small toy model was investigated to examine the underlying mechanism. • The MA optimized strategy exhibits a moderate assortative pattern. • A novel coupling coefficient index was proposed to quantify coupling preference. - Abstract: Recently, the robustness of interconnected networks has attracted extensive attentions, one of which is to investigate the influence of coupling preference. In this paper, the memetic algorithm (MA) is employed to optimize the coupling links of interconnected networks. Afterwards, a comparison is made between MA optimized coupling strategy and traditional assortative, disassortative and random coupling preferences. It is found that the MA optimized coupling strategy with a moderate assortative value shows an outstanding performance against cascading failures on both synthetic scale-free interconnected networks and real-world networks. We then provide an explanation for this phenomenon from a micro-scope point of view and propose a coupling coefficient index to quantify the coupling preference. Our work is helpful for the design of robust interconnected networks.

  14. Amplification of asynchronous inhibition-mediated synchronization by feedback in recurrent networks.

    Directory of Open Access Journals (Sweden)

    Sashi Marella

    2010-02-01

    Full Text Available Synchronization of 30-80 Hz oscillatory activity of the principle neurons in the olfactory bulb (mitral cells is believed to be important for odor discrimination. Previous theoretical studies of these fast rhythms in other brain areas have proposed that principle neuron synchrony can be mediated by short-latency, rapidly decaying inhibition. This phasic inhibition provides a narrow time window for the principle neurons to fire, thus promoting synchrony. However, in the olfactory bulb, the inhibitory granule cells produce long lasting, small amplitude, asynchronous and aperiodic inhibitory input and thus the narrow time window that is required to synchronize spiking does not exist. Instead, it has been suggested that correlated output of the granule cells could serve to synchronize uncoupled mitral cells through a mechanism called "stochastic synchronization", wherein the synchronization arises through correlation of inputs to two neural oscillators. Almost all work on synchrony due to correlations presumes that the correlation is imposed and fixed. Building on theory and experiments that we and others have developed, we show that increased synchrony in the mitral cells could produce an increase in granule cell activity for those granule cells that share a synchronous group of mitral cells. Common granule cell input increases the input correlation to the mitral cells and hence their synchrony by providing a positive feedback loop in correlation. Thus we demonstrate the emergence and temporal evolution of input correlation in recurrent networks with feedback. We explore several theoretical models of this idea, ranging from spiking models to an analytically tractable model.

  15. Robust short-term memory without synaptic learning.

    Directory of Open Access Journals (Sweden)

    Samuel Johnson

    Full Text Available Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds. The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

  16. Robust short-term memory without synaptic learning.

    Science.gov (United States)

    Johnson, Samuel; Marro, J; Torres, Joaquín J

    2013-01-01

    Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

  17. Robust Short-Term Memory without Synaptic Learning

    Science.gov (United States)

    Johnson, Samuel; Marro, J.; Torres, Joaquín J.

    2013-01-01

    Short-term memory in the brain cannot in general be explained the way long-term memory can – as a gradual modification of synaptic weights – since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings. PMID:23349664

  18. A Novel Synchronization-Based Approach for Functional Connectivity Analysis

    Directory of Open Access Journals (Sweden)

    Angela Lombardi

    2017-01-01

    Full Text Available Complex network analysis has become a gold standard to investigate functional connectivity in the human brain. Popular approaches for quantifying functional coupling between fMRI time series are linear zero-lag correlation methods; however, they might reveal only partial aspects of the functional links between brain areas. In this work, we propose a novel approach for assessing functional coupling between fMRI time series and constructing functional brain networks. A phase space framework is used to map couples of signals exploiting their cross recurrence plots (CRPs to compare the trajectories of the interacting systems. A synchronization metric is extracted from the CRP to assess the coupling behavior of the time series. Since the functional communities of a healthy population are expected to be highly consistent for the same task, we defined functional networks of task-related fMRI data of a cohort of healthy subjects and applied a modularity algorithm in order to determine the community structures of the networks. The within-group similarity of communities is evaluated to verify whether such new metric is robust enough against noise. The synchronization metric is also compared with Pearson’s correlation coefficient and the detected communities seem to better reflect the functional brain organization during the specific task.

  19. Synchronous Databus Network in ITER: Open source real-time network for the next nuclear fusion experiment

    International Nuclear Information System (INIS)

    Boncagni, L.; Centioli, C.; Iannone, F.; Neri, C.; Panella, M.; Pangione, L.; Riva, M.; Scappaticci, M.; Vitale, V.; Zaccarian, L.

    2008-01-01

    The next nuclear fusion experiment, ITER, is providing the infrastructure for the optimal operation of a burning plasma, requiring feedback control of discharge parameters and on-line evaluation of computationally intensive models running in a cluster of controller nodes. Thus, the synchronization of the available information on the plasma and plant state variables among the controller nodes is a key issue for ITER. The ITER conceptual design aims to perform feedback control on a cluster of distributed controllers connected by a Synchronous Databus Network (SDN). Therefore it is mandatory to achieve a deterministic data exchange among the controller nodes with a refresh rate of at least 1 kHz and a jitter of at least 50 μs. Thus, a conservative estimate of the data flow within the controller network can be 3 kSample/ms. In this paper the open source RTnet project is evaluated to meet the requirements of the SDN of ITER. A testbed involving a cluster of eight nodes connected over a standard ethernet network has been set up to simulate a distributed real-time control system. The main goal of the test is to verify the compliance of the performance with the ITER SDN requirements

  20. Synchronization of stochastic delayed neural networks with markovian switching and its application.

    Science.gov (United States)

    Tang, Yang; Fang, Jian-An; Miao, Qing-Ying

    2009-02-01

    In this paper, the problem of adaptive synchronization for a class of stochastic neural networks (SNNs) which involve both mixed delays and Markovian jumping parameters is investigated. The mixed delays comprise the time-varying delays and distributed delays, both of which are mode-dependent. The stochastic perturbations are described in terms of Browian motion. By the adaptive feedback technique, several sufficient criteria have been proposed to ensure the synchronization of SNNs in mean square. Moreover, the proposed adaptive feedback scheme is applied to the secure communication. Finally, the corresponding simulation results are given to demonstrate the usefulness of the main results obtained.