Secure communication based on the synchronous control of hysteretic chaotic neuron

Xu, Guowei; Xu, Jixiang; Xiu, Chunbo; Liu, Fengnan; Zang, Yakun

doi:10.1016/j.neucom.2016.08.100

Cited by 30 publications

(4 citation statements)

References 22 publications

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“…Finally, we constructed an energy function to optimize the calculation based on the CNN, providing a new approach to solving the TSP problem. Since chaotic system and chaotic neural network have been widely used in image encryption [36][37][38][39][40] and secure communication [41][42][43][44], the application of these two aspects will be the focus of our future research.…”

Section: Discussionmentioning

confidence: 99%

Dynamic Analysis and FPGA Implementation of New Chaotic Neural Network and Optimization of Traveling Salesman Problem

Cui

Chen

2021

Complexity

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A neural network is a model of the brain’s cognitive process, with a highly interconnected multiprocessor architecture. The neural network has incredible potential, in the view of these artificial neural networks inherently having good learning capabilities and the ability to learn different input features. Based on this, this paper proposes a new chaotic neuron model and a new chaotic neural network (CNN) model. It includes a linear matrix, a sine function, and a chaotic neural network composed of three chaotic neurons. One of the chaotic neurons is affected by the sine function. The network has rich chaotic dynamics and can produce multiscroll hidden chaotic attractors. This paper studied its dynamic behaviors, including bifurcation behavior, Lyapunov exponent, Poincaré surface of section, and basins of attraction. In the process of analyzing the bifurcation and the basins of attraction, it was found that the network demonstrated hidden bifurcation phenomena, and the relevant properties of the basins of attraction were obtained. Thereafter, a chaotic neural network was implemented by using FPGA, and the experiment proved that the theoretical analysis results and FPGA implementation were consistent with each other. Finally, an energy function was constructed to optimize the calculation based on the CNN in order to provide a new approach to solve the TSP problem.

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Section: Discussionmentioning

confidence: 99%

Dynamic Analysis and FPGA Implementation of New Chaotic Neural Network and Optimization of Traveling Salesman Problem

Cui

Chen

2021

Complexity

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“…In this paper, chaotic and confidential communication is achieved using chaotic masking (Ravindran and Nithiyanantham, 2020) based on coupled synchronous control (Xu et al , 2017). Figure 17 shows the driver circuit and Figure 18 shows the response circuit.…”

Section: The Application Of a Chaotic System In Secure Communicationmentioning

confidence: 99%

Five-dimensional memristive Hopfield neural network dynamics analysis and its application in secure communication

Yin

Chen²,

Yu³

et al. 2022

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Purpose This study aims to improve the complexity of chaotic systems and the security accuracy of information encrypted transmission. Applying five-dimensional memristive Hopfield neural network (5D-HNN) to secure communication will greatly improve the confidentiality of signal transmission and greatly enhance the anticracking ability of the system. Design/methodology/approach Chaos masking: Chaos masking is the process of superimposing a message signal directly into a chaotic signal and masking the signal using the randomness of the chaotic output. Synchronous coupling: The coupled synchronization method first replicates the drive system to get the response system, and then adds the appropriate coupling term between the drive The synchronization error and the coupling term of the system will eventually converge to zero with time. The synchronization error and coupling term of the system will eventually converge to zero over time. Findings A 5D memristive neural network is obtained based on the original four-dimensional memristive neural network through the feedback control method. The system has five equations and contains infinite balance points. Compared with other systems, the 5D-HNN has rich dynamic behaviors, and the most unique feature is that it has multistable characteristics. First, its dissipation property, equilibrium point stability, bifurcation graph and Lyapunov exponent spectrum are analyzed to verify its chaotic state, and the system characteristics are more complex. Different dynamic characteristics can be obtained by adjusting the parameter k. Originality/value A new 5D memristive HNN is proposed and used in the secure communication

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“…However, it is still possible to modify the behavior of such systems by means of a proper control input. This fact is the basis of successful applications in fields as optics [7][8][9][10], secure communications [11][12][13][14][15][16][17][18][19][20][21][22][23], finance [5,[24][25][26][27][28], power systems [29][30][31][32][33], electrical machinery [34][35][36], and so on.…”

Section: Introductionmentioning

confidence: 99%

Stabilization and Synchronization of Uncertain Zhang System by Means of Robust Adaptive Control

Pérez-Cruz

2018

Complexity

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Standard adaptive control is the preferred approach for stabilization and synchronization of chaotic systems when the structure of such systems is a priori known but the parameters are unknown. However, in the presence of unmodeled dynamics and/or disturbance, this approach is not effective anymore due to the drift of the parameter estimations, which eventually causes the instability of the closed-loop system. In this paper, a robustifying term, which consists of a saturation function, is used to avoid this problem. The robustifying term is added to the adaptive control law. Consequently, the learning law is also modified. The boundedness of the states and the parameter estimations is rigorously and thoroughly proven by means of Lyapunov like analysis based on Barbalat’s lemma. On these new conditions, the convergence to zero cannot be achieved due to the presence of unmodeled dynamics and/or disturbance. However, it is still possible to guarantee the asymptotic convergence to a bounded zone around zero. The width of this zone can be adjusted by the designer. The performance of this robust approach is verified by numerical simulations. Although, for simplicity, this strategy is only applied to the stabilization and synchronization of Zhang system, the procedure can easily be generalized to a broad class of chaotic systems.

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Secure communication based on the synchronous control of hysteretic chaotic neuron

Cited by 30 publications

References 22 publications

Dynamic Analysis and FPGA Implementation of New Chaotic Neural Network and Optimization of Traveling Salesman Problem

Dynamic Analysis and FPGA Implementation of New Chaotic Neural Network and Optimization of Traveling Salesman Problem

Five-dimensional memristive Hopfield neural network dynamics analysis and its application in secure communication

Stabilization and Synchronization of Uncertain Zhang System by Means of Robust Adaptive Control

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