Adaptive Pinning Synchronization of Fractional Complex Networks with Impulses and Reaction–Diffusion Terms

Hai, Xudong; Ren, Guojian; Yu, Yongguang; Xu, Conghui

doi:10.3390/math7050405

Cited by 7 publications

(3 citation statements)

References 44 publications

(62 reference statements)

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“…A large number of studies have been demonstrated that the node degree of numerous actual networks obey paw-law distribution [62][63][64]. The cumulative distribution function of node degree is defined as:…”

Section: Node Degree Distributionmentioning

confidence: 99%

Dynamic Properties of Foreign Exchange Complex Network

et al. 2019

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The foreign exchange (FX) market, one of the important components of the financial market, is a typical complex system. In this paper, by resorting to the complex network method, we use the daily closing prices of 41 FX markets to build the dynamical networks and their minimum spanning tree (MST) maps by virtue of a moving window correlation coefficient. The properties of FX networks are characterized by the normalized tree length, node degree distributions, centrality measures and edge survival ratios. Empirical results show that: (i) the normalized tree length plays a role in identifying crises and is negatively correlated with the market return and volatility; (ii) 83% of FX networks follow power-law node degree distribution, which means that the FX market is a typical heterogeneous market, and a few hub nodes play key roles in the market; (iii) the highest centrality measures reveal that the USD, EUR and CNY are the three most powerful currencies in FX markets; and (iv) the edge survival ratio analysis implies that the FX structure is relatively stable.

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Section: Node Degree Distributionmentioning

confidence: 99%

Dynamic Properties of Foreign Exchange Complex Network

et al. 2019

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“…In the existing work of outer synchronization in complex networks, one usually designs some suitable control protocols to drive the synchronization of networks. To reduce control costs, some feasible control methods have been proposed, such as intermittent control [15][16][17][18][19][20][21][22], impulsive control [23,24], event-triggered control [25][26][27], pinning control [14,[28][29][30][31][32][33], and so on.…”

Section: Introductionmentioning

confidence: 99%

Outer Synchronization of Two Muti-Layer Dynamical Complex Networks with Intermittent Pinning Control

2023

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This paper regards the outer synchronization of multi-layer dynamical networks with additive couplings via aperiodically intermittent pinning control, in which different layers of each multi-layer network have different topological structures. First, a state-feedback intermittent pinning controller is designed in the drive and response configuration, and sufficient conditions to achieve the outer synchronization are derived based on the Lyapunov stability theory and matrix inequalities. Second, outer synchronization problem of multi-layer networks is discussed by setting an adaptive intermittent pinning controller; an appropriate Lyapunov function is selected to prove the criteria of synchronization between the drive multi-layer network and the response multi-layer network. Finally, three simulation examples are given to show the effectiveness of our control schemes.

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“…Fixed-time synchronization of neural networks by designing a new controller. In recent decades, researchers have proposed many different control methods to stabilise various systems, such as adaptive control [18], pinning control [19,20], intermittent control [21] and sliding mode control [22,23]. As intermittent control has a discontinuous working time, control costs can be reduced.…”

Section: Introductionmentioning

confidence: 99%

Fixed-Time Synchronization of Neural Networks Based on Quantized Intermittent Control for Image Protection

et al. 2021

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This paper considers the fixed-time synchronization (FIXTS) of neural networks (NNs) by using quantized intermittent control (QIC). Based on QIC, a fixed-time controller is designed to ensure that the NNs achieve synchronization in finite time. With this controller, the settling time can be estimated regardless of initial conditions. After ensuring that the system has stabilized through this strategy, it is suitable for image protection given the behavior of the system. Meanwhile, the encryption effect of the image depends on the encryption algorithm, and the quality of the decrypted image depends on the synchronization error of NNs. The numerical results show that the designed controller is effective and validate the practical application of FIXTS of NNs in image protection.

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Adaptive Pinning Synchronization of Fractional Complex Networks with Impulses and Reaction–Diffusion Terms

Cited by 7 publications

References 44 publications

Dynamic Properties of Foreign Exchange Complex Network

Dynamic Properties of Foreign Exchange Complex Network

Outer Synchronization of Two Muti-Layer Dynamical Complex Networks with Intermittent Pinning Control

Fixed-Time Synchronization of Neural Networks Based on Quantized Intermittent Control for Image Protection

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