Mean square modified function projective synchronization of uncertain complex network with multi-links and stochastic perturbations

Zhao, Hui; Li, Lixiang; Peng, Haipeng; Xiao, Jinghua; Yang, Yixian

doi:10.1140/epjb/e2014-50577-2

Cited by 21 publications

(3 citation statements)

References 25 publications

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“…Complex networks (CNs) are effective system modeling tools in the real world, every network can be described in terms of nodes and edges, where each edge represents a connection between nodes. Multi-link networks [1][2][3] are the networks that have more than one connection between two nodes. There are numerous multilink networks in life, such as relationship networks, transportation networks, and communication networks.…”

Section: Introductionmentioning

confidence: 99%

Finite-time complex projective synchronization of fractional-order complex-valued uncertain multi-link network and its image encryption application

Hu¹,

Yang²,

Ding³

et al. 2022

Chinese Phys. B

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Multi-links networks are universal in real world such as relationship networks, transportation networks and communication networks. It is significant to investigate the synchronization of the network with multi-links. In this paper, considering the complex network with uncertain parameters, new adaptive controller and update laws are proposed to ensure that complex-valued multi-links network realizes finite-time complex projective synchronization (FTCPS). In addition, based on fractional-order Lyapunov functional method and finite-time stability theory, the criteria of FTCPS are derived and synchronization time is given which is associated with fractional order and control parameters. Meanwhile, numerical example is given to verify the validity of proposed finite-time complex projection strategy and analyze the relationship between synchronization time and fractional order and control parameters. Finally, the network is applied to image encryption and security analysis is carried out to verify the correctness of this method.

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Section: Introductionmentioning

confidence: 99%

Finite-time complex projective synchronization of fractional-order complex-valued uncertain multi-link network and its image encryption application

Hu¹,

Yang²,

Ding³

et al. 2022

Chinese Phys. B

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“…In particular, the synchronization of CDNs is an interesting research direction since it is a typical collective behavior in nature. And, as various unexpected factors will disturb the systems in practical applications, many efforts have been made to obtain the synchronization of systems in the cases of time-delays [6]- [10], nonlinear couplings [11]- [15], uncertainties and disturbances [16]- [22], etc. therefore, the research on the synchronization control and CDNs has theoretical significance and practical prospect, which motivates our work.…”

Section: Introductionmentioning

confidence: 99%

Finite-Time ${H_\infty}$ Fault-Tolerant Synchronization Control for Complex Dynamical Networks With Actuator Faults

Liu

Chen

et al. 2019

IEEE Access

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This paper focuses on the problem of finite-time H ∞ fault tolerant synchronization control for complex dynamical network with actuator faults. By using the prior knowledge of the actuator faults, the complex dynamical network with actuator faults is described as a complex dynamical network with parameter uncertainties. By using some tools to deal with the Laypunov functional, a sufficient condition is obtained. Finally, an example is given to demonstrate the validity of the main results. INDEX TERMS Complex dynamical networks, fault-tolerant control, actuator faults, finite-time H ∞ synchronization.

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“…In the applications, there are typically some uncertain parameters and noise perturbations in real systems, which often affect their dynamics, so it has practical implications to investigate synchronization issues of uncertain complex dynamical networks by using a pinning control strategy [17] and adaptive control [18][19][20]. To our best knowledge, the memristor-based neural networks models proposed and studied in the literature are deterministic.…”

Section: Introductionmentioning

confidence: 99%

Anti-synchronization for stochastic memristor-based neural networks with non-modeled dynamics via adaptive control approach

Zhao

Peng

et al. 2015

Eur. Phys. J. B

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In this paper, exponential anti-synchronization in mean square of an uncertain memristor-based neural network is studied. The uncertain terms include non-modeled dynamics with boundary and stochastic perturbations. Based on the differential inclusions theory, linear matrix inequalities, Gronwall's inequality and adaptive control technique, an adaptive controller with update laws is developed to realize the exponential anti-synchronization. Adaptive controller can adjust itself behavior to get the best performance, according to the environment is changing or the environment has changed, which has the ability to adapt to environmental change. Furthermore, a numerical example is provided to validate the effectiveness of the proposed method.

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Mean square modified function projective synchronization of uncertain complex network with multi-links and stochastic perturbations

Cited by 21 publications

References 25 publications

Finite-time complex projective synchronization of fractional-order complex-valued uncertain multi-link network and its image encryption application

Finite-time complex projective synchronization of fractional-order complex-valued uncertain multi-link network and its image encryption application

Finite-Time ${H_\infty}$ Fault-Tolerant Synchronization Control for Complex Dynamical Networks With Actuator Faults

Anti-synchronization for stochastic memristor-based neural networks with non-modeled dynamics via adaptive control approach

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