Memristive Autapse-Coupled Neuron Model With External Electromagnetic Radiation Effects

Zhang, Sen; Li, Chunbiao; Zheng, Jiahao; Wang, Xiaoping; Zeng, Zhigang; Chen, Guanrong

doi:10.1109/tie.2022.3225847

Cited by 39 publications

(5 citation statements)

References 33 publications

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“…Due to the inherent randomness and unpredictability, chaotic signals are considered one of the most promising candidates for image encryption. Over the past few decades, achieving chaos control to realize more efficient encryption methods has become a hot topic [24][25][26]. The commonly used methods include offset boosting control and amplitude control.…”

Section: Introductionmentioning

confidence: 99%

Further study on the Rulkov neuron: geometric control, circuit realization and chaos-based encryption

Xia,

Li,

et al. 2024

Phys. Scr.

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Rulkov neuron with various firing modes is exhaustively explored by numerical simulation aiming to disclose its unique properties of evolution. Transient chaos and the coexistence of periodic state and chaos are found. Furthermore, it is found that the chaotic attractors in the neuron can also be arranged flexibly in phase space by a single offset booster, while the amplitude of firings is rescaled by an independent amplitude controller. Circuit implementation based on MCU is carried out demonstrating the predicted dynamics. Confidentiality and security of data play an important role in safeguarding national production and livelihood. In this paper, the chaotic firing is introduced into the Tiny Encryption Algorithm (TEA) for image encryption based on MCU combined with metrics analysis. It is proven that the Chaos-based Tiny Encryption Algorithm (ChaosTEA) exhibits higher efficiency and security compared to the traditional TEA algorithm.

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Section: Introductionmentioning

confidence: 99%

Further study on the Rulkov neuron: geometric control, circuit realization and chaos-based encryption

Xia,

Li,

et al. 2024

Phys. Scr.

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“…Chen et al [19] used a memristor as a coupling synapse to connect two FHN neurons, they found that the resultant system can exhibit hidden extreme multistability. Zhang et al [25] proposed a novel memristive autapse-coupled neuron model with external electromagnetic radiation, they found that the system can not only produce multiple numbers of grid multi-scroll hidden attractors, but also generate rich and complex hidden firing dynamics. Tan et al [26] coupled two 2D HR neurons with a locally active nonvolatile memristor and found that complex firing activity occurred only within the locally active region of the memristor.…”

Section: Introductionmentioning

confidence: 99%

Switchable memristor-based Hindmarsh-Rose neuron under electromagnetic radiation

Zhang,

2024

Nonlinear Dyn

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Memristors are prevalently used to simulate biological neuronal synapses due to their unique memductance plasticity and memory effects. A new switchable memristor, which can be configured as a nonvolatile discrete memristor, a nonvolatile continuum memristor or a volatile memristor by adjusting its internal parameter, is proposed to mimic the autapse of the Hindmarsh-Rose (HR) neuron. In the meantime, a flux-controlled memristor is introduced to simulate the effect of external electromagnetic radiation on the HR neuron, thus, an improved 4D HR neuron model without equilibrium points is developed in this study. The hidden firing activities related to the strength of autapse and the electromagnetic radiation intensity are revealed through phase diagrams, time series, bifurcation diagrams, Lyapunov exponent spectrums, and two-parameter dynamical maps. More interestingly, it is found that the memory attributes of memristive autapse play an important role in the firing activities of the neuron, which can induce the mutual transition among periodic spiking with different frequencies and chaotic firing. Additionally, the transition between periodic and chaotic firing induced by the initial value of the switchable memristor is also discovered when it is configured as three different types of memristors. Finally, a neuron circuit is designed with the current-mode devices to improve accuracy and reduce power consumption. The Multisim simulation results are provided to validate the correctness of the neuron model and the effectiveness of numerical analysis.

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“…LAM has great potential for application in constructing memristive neuron and neural network models [31][32][33]. LAM is able to simulate synapse between neurons and electromagnetic radiation received by neurons.…”

Section: Introductionmentioning

confidence: 99%

Dynamical analysis of a discrete Aihara neuron under a locally active memristor as electromagnetic radiation and its DSP implementation

Cao,

et al. 2024

Phys. Scr.

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The study of neuron model under electromagnetic radiation is significant for learning brain principles and treating mental diseases. In this paper, a novel discrete locally active memristor(DLAM) model is designed and its characteristics are investigated thoroughly. Then, the DLAM is used to imitate electromagnetic radiation to stimulate Aihara neuron, called EMR-Aihara neuron model. The equilibrium point of this discrete model is analyzed. Dynamical characteristics are studied by means of phase diagram, iteration sequence, bifurcation diagram, Lyapunov Exponent spectrum(LEs), Kolmogorow entropy(KE) and Spectral Entropy(SE) complexity. With these analysis methods, rich dynamical behaviors and neuron firing patterns are discovered from the EMR-Aihara neuron map, including hyperchaos, chaos and period. In addition, complex multistability and state transition phenomena concerning various attractors and neuron firing modes are observed. This EMR-Aihara neuron map is implemented in digital circuit by DSP platform as well, confirming the physical availability of the model. The EMR-Aihara neuron model can simulate biological neuron under electromagnetic radiation and apply to image encryption.

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Memristive Autapse-Coupled Neuron Model With External Electromagnetic Radiation Effects

Cited by 39 publications

References 33 publications

Further study on the Rulkov neuron: geometric control, circuit realization and chaos-based encryption

Further study on the Rulkov neuron: geometric control, circuit realization and chaos-based encryption

Switchable memristor-based Hindmarsh-Rose neuron under electromagnetic radiation

Dynamical analysis of a discrete Aihara neuron under a locally active memristor as electromagnetic radiation and its DSP implementation

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