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Electromagnetic induction effect caused by neuron potential can be mimicked using memristor. This paper considers a fluxcontrolled memristor to imitate the electromagnetic induction effect of adapting feedback synapse and presents a memristive neuron model with the adapting synapse. The memristive neuron model is three-dimensional and non-autonomous. It has the time-varying equilibria with multiple stabilities, which results in the global coexistence of multiple firing patterns. Multiple numerical plots are executed to uncover diverse coexisting firing patterns in the memristive neuron model. Particularly, a nonlinear fitting scheme is raised and a fitting activation function circuit is employed to implement the memristive mono-neuron model. Diverse coexisting firing patterns are observed from the hardware experiment circuit and the measured results verify the numerical simulations well. 相似文献
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Initial-dependent extreme multi-stability and offset-boosted coexisting attractors have been significantly concerned recently.This paper constructs a novel five-dimensional(5-D) two-memristor-based dynamical system by introducing two memristors with cosine memductance into a three-dimensional(3-D) linear autonomous dissipative system. Through theoretical analyses and numerical plots, the memristor initial-boosted coexisting plane bifurcations are found and the memristor initial-dependent extreme multi-stability is revealed in such a two-memristor-based dynamical system with plane equilibrium. Furthermore, a dimensionality reduction model with the determined equilibrium is established via an integral transformation method, upon which the memristor initial-dependent extreme multi-stability is reconstituted theoretically and expounded numerically. Finally,physically circuit-implemented PSIM(power simulation) simulations are carried out to validate the plane offset-boosted coexisting behaviors. 相似文献
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