Related references
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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
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Minglin Ma et al.
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ELECTRONICS LETTERS
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Ziwei Liang et al.
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Shaobo He et al.
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Chunlai Li et al.
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Zhao Yao et al.
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NONLINEAR DYNAMICS
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Ling Zhou et al.
Summary: This paper investigates a simple memristor emulator consisting of a diode bridge and a capacitor, and demonstrates its pinched hysteresis loops and higher operating frequency. Through mathematical modeling, it is found that the system only possesses one unstable equilibrium point, and various bifurcations, periodic and chaotic orbits, and coexisting attractors are depicted.
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Yanmei Lu et al.
Summary: This paper investigates the features of memristive-coupled neural networks in the discrete field, and introduces a discrete memristor with sine-type conductance for the first time. The properties of the proposed memristive-coupled bi-neuron Rulkov map and multi-neuron Rulkov neural network are probed using numerical simulation methods, revealing the effects of parameters and coupling factors on the dynamics of the system.
NETWORK-COMPUTATION IN NEURAL SYSTEMS
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Zhenghui Wen et al.
Summary: This paper investigates the effect of magnetic field coupling between neurons on neuron dynamics and finds that it can change the firing mode of neurons, providing new insights into the mechanism of information interaction between neurons.
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Hui Shen et al.
Summary: This paper proposes a novel memristor that is applied to construct neurons and neural networks. By conducting a series of analysis and experiments, the paper verifies its performance in terms of firing dynamics and compares different firing patterns and coupled neural networks. The research results are of great significance for revealing the mystery of the brain and potential applications in practical projects.
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Chengjie Chen et al.
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