Oscillator death in coupled functional differential equations near Hopf bifurcation

The stability of the equilibrium solution is analyzed for coupled systems of retarded functional differential equations near a supercritical Hopf bifurcation. Necessary and sufficient conditions are derived for asymptotic stability under general coupling conditions. It is shown that the largest eigenvalue of the graph Laplacian completely characterizes the effect of the connection topology on the stability of diffusively and symmetrically coupled identical systems. In particular, all bipartite graphs have identical stability characteristics regardless of their size. Furthermore, bipartite graphs and large complete graphs provide, respectively, lower and upper bounds for the parametric stability regions for arbitrary connection topologies. Generalizations are given for networks with asymmetric coupling. The results characterize the connection topology as a mechanism for the death of coupled oscillators near Hopf bifurcation.     

Synchronization of neural networks based on parameter identification and via output or state coupling

For neural networks with all the parameters unknown, we focus on the global robust synchronization between two coupled neural networks with time-varying delay that are linearly and unidirectionally coupled. First, we use Lyapunov functionals 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 robust synchronization regardless of their initial states. Second, by employing the invariance principle of functional differential equations, a simple, analytical, and rigorous adaptive feedback scheme is proposed for the robust synchronization of almost all kinds of coupled neural networks with time-varying delay based on the parameter identification of uncertain delayed neural networks. Finally, numerical simulations validate the effectiveness and feasibility of the proposed technique.     

Failure risk propagation and protection schemes in coupled systems

Many modern systems have the property of coupling, which weakens the system against the outburst of failure. The risks to fail in a single layer may propagate to the entire system through inter-layer connections. In the field of propagation process, the existing literatures mainly focus on the global phenomena in coupled systems through some statistic methods, the dynamical evolution of failure risk propagation and the protection schemes for coupled systems are seldom mentioned. In this paper, we model the coupled systems using six types of coupled networks, over which the failure risk propagation occurs. Then, three cellular automata (CA) models are performed to describe the protection schemes in case of failure risk propagation. Based on a newly presented measurement, a series of experiments are conducted on the coupled networks as well as the single-layered networks, where the propagation processes with and without protection schemes are demonstrated. The results show that the failure risk propagation varies depending on the type and structure of the coupled networks. Moreover, with a small fraction of nodes protected based on some immunization strategies, the system’s robustness to the failure risk propagation is highly improved.     

Generalized synchronization between two different complex networks

In this paper, generalized synchronization (GS) between two coupled complex networks is theoretically and numerically studied, where the node vectors in different networks are not the same, and the numbers of nodes of both networks are not necessarily equal. First, a sufficient criterion for GS, one kind of outer synchronizations, of two coupled networks is established based on the auxiliary system method and the Lyapunov stability theory. Numerical examples are also included which coincide with the theoretical analysis.     

Exponential synchronization of stochastic fuzzy cellular neural networks with time delay in the leakage term and reaction-diffusion

Separate studies have been published on the stability of fuzzy cellular neural networks with time delay in the leakage term and synchronization issue of coupled chaotic neural networks with stochastic perturbation and reaction-diffusion effects. However, there have not been studies that integrate the two fields. Motivated by the achievements from both fields, this paper considers the exponential synchronization problem of coupled chaotic fuzzy cellular neural networks with stochastic noise perturbation, time delay in the leakage term and reaction-diffusion effects using linear feedback control. Lyapunov stability theory combining with stochastic analysis approaches are employed to derive sufficient criteria ensuring the coupled chaotic fuzzy neural networks to be exponentially synchronized. This paper also presents an illustrative example and uses simulated results of this example to show the feasibility and effectiveness of the proposed scheme.     

Global exponential stability for a class of retarded functional differential equations with applications in neural networks

In this paper, the global exponential stability and asymptotic stability of retarded functional differential equations with multiple time-varying delays are studied by employing several Lyapunov functionals. A number of sufficient conditions for these types of stability are presented. Our results show that these conditions are milder and more general than previously known criteria, and can be applied to neural networks with a broad range of activation functions assuming neither differentiability nor strict monotonicity. Furthermore, the results obtained for neural networks with time-varying delays do not assume symmetry of the connection matrix.     

An intriguing hybrid synchronization phenomenon of two coupled complex networks

This paper investigates the hybrid synchronization problem of two coupled complex networks. Employing the linear feedback and the adaptive feedback control methods which are simple, efficient, and easy to implement in practical applications, we obtain some useful criteria of the hybrid synchronization of two coupled networks based on the Lyapunov stability theory and Lasalle’s invariance principle. It shows that under suitable conditions, two coupled complex networks can realize an intriguing hybrid synchronization: the outer anti-synchronization between the driving network and the response network, and the inner complete synchronization in the driving network and the response network, respectively. Numerical simulations demonstrate the effectiveness of the proposed hybrid synchronization scheme.     

A scheme of de-synchronization in globally coupled neural networks and its possible implications for vagus nerve stimulation

A scheme of de-synchronization via pulse stimulation is numerically investigated in the Hindmarsh Rose globally coupled neural networks. The simulations show that synchronization evolves into de-synchronization in the globally coupled HR neural network when a part (about 10%) of neurons are stimulated with a pulse current signal. The network de-synchronization appears to be sensitive to the stimulation parameters. For the case of the same stimulation intensity, those weakly coupled networks reach de-synchronization more easily than strongly coupled networks. There exists a homologous asymptotic behavior in the region of higher frequency, and exist the optimal stimulation interval and period of continuous stimulation time when other stimulation parameters remain invariable.     

Dynamics of Coupled Cell Networks: Synchrony, Heteroclinic Cycles and Inflation

We consider the dynamics of small networks of coupled cells. We usually assume asymmetric inputs and no global or local symmetries in the network and consider equivalence of networks in this setting; that is, when two networks with different architectures give rise to the same set of possible dynamics. Focussing on transitive (strongly connected) networks that have only one type of cell (identical cell networks) we address three questions relating the network structure to dynamics. The first question is how the structure of the network may force the existence of invariant subspaces (synchrony subspaces). The second question is how these invariant subspaces can support robust heteroclinic attractors. Finally, we investigate how the dynamics of coupled cell networks with different structures and numbers of cells can be related; in particular we consider the sets of possible “inflations” of a coupled cell network that are obtained by replacing one cell by many of the same type, in such a way that the original network dynamics is still present within a synchrony subspace. We illustrate the results with a number of examples of networks of up to six cells.     

Viscosity Solutions of Monotonic Functional Parabolic PDE

In this paper,by the technique of coupled solutions,the notion of viscosity solution is ex-tended to quasi-monotonic fully nonlinear parabolic equations with delay,which involves many modelsarising from optimal control theory,economy and finance,biology etc.The comparison,existence anduniqueness are proved.And the results are applied to the retarded Bellman equations.     

Approximation of eigenvalues of evolution operators for linear coupled renewal and retarded functional differential equations

Ricerche di Matematica - Recently, systems of coupled renewal and retarded functional differential equations have begun to play a central role in complex and realistic models of population...     

Adaptive synchronization of two nonlinearly coupled complex dynamical networks with delayed coupling

This paper investigates the adaptive synchronization between two nonlinearly delay-coupled complex networks with the bidirectional actions and nonidentical topological structures. Based on LaSalle’s invariance principle, some criteria for the synchronization between two coupled complex networks are achieved via adaptive control. To validate the proposed methods, the unified chaotic system as the nodes of the networks are analyzed in detail, and numerical simulations are given to illustrate the theoretical results.     

A graph‐theoretic method to stabilize the delayed coupled systems on networks based on periodically intermittent control

This paper mainly focus on the exponential stabilization problem of coupled systems on networks with mixed time‐varying delays. Periodically intermittent control is used to control the coupled systems on networks with mixed time‐varying delays. Moreover, based on the graph theory and Lyapunov method, two different kinds of stabilization criteria are derived, which are in the form of Lyapunov‐type theorem and coefficients‐type criterion, respectively. These laws reveal that the stability has a close relationship with the topology structure of the networks. In addition, as a subsequent result, a decision theorem is also presented. It is straightforward to show the stability of original system can be determined by that of modified system with added absolute value into the coupling weighted‐value matrix. Finally, the feasibility and validity of the obtained results are demonstrated by several numerical simulation figures.     

时变耦合变时滞非自治神经网络模型的全局同步性分析

利用Lyapunov泛函方法,对一类时变线性耦合神经网络模型的全局同步性进行了研究．在去掉耦合矩阵的对称性、不可约性和扩散耦合限制的基础上,得到了确保耦合时滞神经网络模型全局同步的充分性条件．所得结果仅依赖于系统中的参数,条件易于验证且不必求矩阵的特征值．     

The wavelet transform method applied to a coupled chaotic system with asymmetric coupling schemes

The wavelet transform method originated by Wei et al. (2002) [19] is an effective tool for enhancing the transverse stability of the synchronous manifold of a coupled chaotic system. Much of the theoretical study on this matter is centered on networks that are symmetrically coupled. However, in real applications, the coupling topology of a network is often asymmetric; see Belykh et al. (2006)  [23], [24], Chavez et al. (2005)  [25], Hwang et al. (2005)  [26], Juang et al. (2007)  [17], and Wu (2003)  [13]. In this work, a certain type of asymmetric sparse connection topology for networks of coupled chaotic systems is presented. Moreover, our work here represents the first step in understanding how to actually control the stability of global synchronization from dynamical chaos for asymmetrically connected networks of coupled chaotic systems via the wavelet transform method. In particular, we obtain the following results. First, it is shown that the lower bound for achieving synchrony of the coupled chaotic system with the wavelet transform method is independent of the number of nodes. Second, we demonstrate that the wavelet transform method as applied to networks of coupled chaotic systems is even more effective and controllable for asymmetric coupling schemes as compared to the symmetric cases.     

Synchronization of fractional‐order delayed neural networks with hybrid coupling

This article presents new theoretical results on the synchronization for a class of fractional‐order delayed neural networks with hybrid coupling that contains constant coupling and discrete‐delay coupling. This is the first attempt to investigate the synchronization problem of fractional‐order coupled delayed neural networks. Based on the fractional‐order Lyapunov stability theorem and Kronecker product properties, sufficient criteria are established to ensure the fractional‐order coupled neural network to achieve synchronization. Numerical simulations are given to illustrate the correctness of the theoretical results. © 2015 Wiley Periodicals, Inc. Complexity 21: 106–112, 2016     

Viscosity Solutions of Monotonic Functional Parabolic PDE

In this paper, by the technique of coupled solutions, the notion of viscosity solution is extended to quasi-monotonic fully nonlinear parabolic equations with delay, which involves many models arising from optimal control theory, economy and finance, biology etc. The comparison, existence and uniqueness are proved, And the results are applied to the retarded Bellman equations.     

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

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.     

Adaptive synchronization of bipartite dynamical networks with distributed delays and nonlinear derivative coupling

This paper investigates the synchronization in a class of bipartite dynamical networks with distributed delays and nonlinear derivative coupling. Based on Lyapunov stability theory, some useful synchronization criteria are established for the two coupled bipartite dynamical networks by constructing effective adaptive feedback controllers and update laws. The numerical simulations are provided to illustrate the effectiveness of the theoretical results obtained in this paper.     

Network science faces the challenge and opportunity:exploring ``Network of Networks" and its unified theoretical framework

In the era of big data, network science is facing new challenges and opportunities. This review article focuses on discussing one of the hottest subjects of network science - ``network of networks" (NON). The main features, several typical examples and the main progress for NON are outlined, including the epidemic spreading in multilayer coupled networks. Finally the most challenging tasks for NON are proposed.