Diffusion and growth in an evolving network

We study a simple model of a population of agents whose interaction network co-evolves with knowledge diffusion and accumulation. Diffusion takes place along the current network and, reciprocally, network formation depends on the knowledge profile. Diffusion makes neighboring agents tend to display similar knowledge levels. On the other hand, similarity in knowledge favors network formation. The cumulative nonlinear effects induced by this interplay produce sharp transitions, equilibrium co-existence, and hysteresis, which sheds some light on why multiplicity of outcomes and segmentation in performance may persist resiliently over time in knowledge-based processes.     

On the partial synchronization of iterative methods

The rapidly growing field of parallel computing systems promotes the study of parallel algorithms, with the Monte Carlo method and asynchronous iterations being among the most valuable types. These algorithms have a number of advantages. There is no need for a global time in a parallel system (no need for synchronization), and all computational resources are efficiently loaded (the minimum processor idle time). The method of partial synchronization of iterations for systems of equations was proposed by the authors earlier. In this article, this method is generalized to include the case of nonlinear equations of the form x = F(x), where x is an unknown column vector of length n, and F is an operator from ?ⁿ into ?ⁿ. We consider operators that do not satisfy conditions that are sufficient for the convergence of asynchronous iterations, with simple iterations still converging. In this case, one can specify such an incidence of the operator and such properties of the parallel system that asynchronous iterations fail to converge. Partial synchronization is one of the effective ways to solve this problem. An algorithm is proposed that guarantees the convergence of asynchronous iterations and the Monte Carlo method for the above class of operators. The rate of convergence of the algorithm is estimated. The results can prove useful for solving high-dimensional problems on multiprocessor computational systems.     

Critical phenomena in evolving networks: Ferromagnetic phase transition in evolving network of stochastic cellular automata

It is shown by MC simulations that ferromagnetic system modeled by cellular automata with synchronously rewired interconnections changes critically when preference in rewiring is added – the system becomes resistant against stochastic noise. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Impulsive synchronization of time-varying dynamical network

Synchronization of time-varying dynamical network is investigated via impulsive control. Based on the Lyapunov function method and stability theory of impulsive differential equation, a synchronization criterion with respect to the system parameters and the impulsive gains and intervals is analytically derived. Further, an adaptive strategy is introduced for designing unified impulsive controllers, with a corresponding synchronization criterion derived. In this proposed adaptive control scheme, the impulsive instants adjust themselves to the needed values as time goes on, and an algorithm for determining the impulsive instants is provided and evaluated. The derived theoretical results are illustrated to be effective by several numerical examples.     

The reactive slab with partial insulation: A lower bound to criticality

Summary The problem of determining critical conditions in a chemically reactive slab when the surface is partially insulated has been examined. A lower bound for the critical Frank-Kamenetskii parameter, which is a function of the insulation width and the activation energy parameter(=R T ₀/E), has been determined. For=0 this bound is identical to that given by Khudyaev's method.

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Zusammenfassung Die Bestimmung der Kritikalität einer Schicht mit chemischer Reaktion und teilweiser Isolierung der Oberfläche wurde untersucht. Ein unterer Grenzwert des kritischen Frank-Kamenetskii Parameter, der von Isolierungbreite und Aktivierungs-Energie-Parameter(=R T ₀/E)abhängt, wurde bestimmt. Für=0 ist dieser Grenzwert identisch mit dem entsprechenden Wert der Khudyaev Methode.

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I am indebted to Dr. D. M. Edwards, Dr. D. M. Herbert and Professor J. Toland for helpful advice.     

Cluster synchronization in community network with hybrid coupling

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.     

On the latest starting times and criticality of activities in a network with imprecise durations

This paper deals with problems of computing possible values of latest starting times and determining types of criticality for all activities in a network with interval or fuzzy activity durations. Although the problem of computing the latest starting times has been solved, a novel polynomial algorithm which is easy to understand and improves complexity is proposed.     

Noise and coupling induced synchronization in a network of chaotic neurons

The synchronization in four forced FitzHugh–Nagumo (FHN) systems is studied, both experimentally and by numerical simulations of a model. We show that synchronization may be achieved either by coupling of systems through bidirectional diffusive interactions, by introducing a common noise to all systems or by combining both ingredients, noise and coupling together. Here we consider white and colored noises, showing that the colored noise is more efficient in synchronizing the systems respect to white noise. Moreover, a small addition of common noise allows the synchronization to occur at smaller values of the coupling strength. When the diffusive coupling in the absence of noise is considered, the system undergoes the transition to subthreshold oscillations, giving a spike suppression regime. We show that noise destroys the appearance of this dynamical regime induced by coupling.     

An approach of partial control design for system control and synchronization

In this paper, a general approach of partial control design for system control and synchronization is proposed. It turns control problems into simpler ones by reducing their control variables. This is realized by utilizing the dynamical relations between variables, which are described by the dynamical relation matrix and the dependence–influence matrix. By adopting partial control theory, the presented approach provides a simple and general way to stabilize systems to their partial or whole equilibriums, or to synchronize systems with their partial or whole states. Further, based on this approach, the controllers can be simplified. Two examples of synchronizing chaotic systems are given to illustrate its effectiveness.     

The computational complexity of the criticality problems in a network with interval activity times

The paper analyzes the criticality in a network with interval activities duration times. A natural generalization of the criticality notion (for a path, an activity and an event) for the case of network with interval activity duration times is given. The computation complexity of five problems linked to the introduced criticality notion is presented.     

Cluster synchronization for directed community networks via pinning partial schemes

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.     

Multistable remote synchronization in a star-like network of non-identical oscillators

In the context of networks of coupled oscillators, remote synchronization happens when phase difference between non-adjacent units become constant, even though there is no global phase-locking. We study such regime considering a star-like network of Stuart-Landau oscillators. As previous works, our setup comprises peripheral nodes with different but close natural frequencies and the central node frequency detuned from them. The main contribution here is to numerically report multistability under intermediate coupling values: some initial condition yield remote synchronization, with quasi-periodic motion; while others do not converge to synchronized states. By using a Gaussian distribution to select the initial phases of the oscillators, we found that relatively small value of the standard deviation and absolute value of the mean of this distribution far from a specific range of values seem to favor remote synchronization in the multistability region. This phenomenon is extensively analyzed for both cases, considering a fixed coupling value.     

Modulation of synchronization dynamics in a network of self-sustained systems

This paper addresses the combined modulatory effects of non-nearest neighbor oscillators and local injection on synchronized states dynamics with their corresponding stability boundaries in a network of self-sustained systems. The Whittaker method and Floquet theory are used to predict analytically the stability of these states for identical and non-identical coupling parameters. Charts revealing the modulation of synchronized states and their stability boundaries at the second order of interaction in the cases of identical and non-identical coupling parameters are constructed with and without an external signal locally injected in the network. Numerical simulations validate and complement the results of analytical surveys. The limits of the stability regions are numerically explored when a small amount of Gaussian white noise is also injected in the network.     

Synchronization of an evolving complex hyper-network

An evolving hyper-network model is proposed for better describing some complex systems. A concept of joint degree is introduced, and the evolving mechanism of the hyper-network is given with respect to the joint degree. The hyper-degree distribution of this evolving hyper-network is derived based on a rate equation method and is shown to obey a power law, non-Gaussian distribution. Furthermore, the synchronization in a hyper-network of coupled dynamical systems is investigated for the first time. By calculating the joint degree matrix, several simple yet useful synchronization criteria are obtained and are illustrated numerically in specific examples.     

Cluster synchronization,switching and spatiotemporal coding in a phase oscillator network

A network of five globally-coupled identical phase oscillators is considered. Cluster states consisting of two synchronized pairs of oscillators and one singleton are investigated. Forcing the system with non-uniform constant inputs results in regular switches between cluster states. The resultant cyclic sequences of switches (spatiotemporal codes) are studied for different initial conditions and input configurations. Implications on information coding in neural systems are briefly discussed. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

On the hardness of evaluating criticality of activities in a planar network with duration intervals

Complexity results for problems of evaluating the criticality of activities in planar networks with duration time intervals are presented. We show that the problems of asserting whether an activity is possibly critical, and of computing bounds on the float of an activity in these networks are NP-complete and NP-hard, respectively.     

Influence of the nearest-neighbor connections on shaping weighted evolving network

This paper proposes an extended local-world evolving network model consisting of global strength-driven preferential attachment for one central node, and local weight-driven preferential attachment for nearest neighbors of the central node. Analytical predictions and numerical simulations were executed for network evolutions and distributions. The obtained power-law behaviors display the same exponent functions as the ones in a classic model. More comparisons between these two models were made to investigate the structural differences that the nearest-neighbor connections result in. Compared with the counterpart, the proposed model shows a higher clustering coefficient, the varying average shortest path length and the significant hierarchical organization. our model is generally robustness and yet fragility, and is weaker in synchronizability than the counterpart. All those results are added to our understanding of how the rule of the nearest-neighbor connections affects the characteristics of weighted evolving network.     

强部分逆网络流问题

Abstract. In this paper,a new model for inverse network flow problems,robust partial inverseproblem is presented. For a given partial solution,the robust partial inverse problem is to modify the coefficients optimally such that all full solutions containing the partial solution becomeoptimal under new coefficients. It has been shown that the robust partial inverse spanning treeproblem can be formulated as a combinatorial linear program,while the robust partial inverseminimum cut problem and the robust partial inverse assignment problem can be solved by combinatorial strongly polynomial algorithms.     

Hybrid synchronization of heterogeneous chaotic systems on dynamic network

For researching the hybrid synchronization of heterogeneous chaotic systems on the complex dynamic network, there are two important issues to be discussed and analyzed. One is how to build a dynamic complex network which the connection between nodes is dynamic. Another is comparing and analyzing the synchronization characteristics of heterogeneous chaotic systems on the dynamic and static complex network. In this paper, the theoretical analysis and numerical simulation are implemented to study the synchronization on different dynamic and static complex networks. The results indicate it is feasible to realize the hybrid synchronization of heterogeneous chaotic systems on the complex dynamic network.     

Impulsive synchronization of a general nonlinear coupled complex network

This paper investigates impulsive synchronization of a general nonlinear coupled complex network. Based on the comparison theory of impulsive differential system, some novel synchronization criteria are derived, and impulsive controllers are designed simultaneously. Finally, numerical simulations demonstrate the effectiveness of the proposed synchronization criteria.