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 ...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.展开更多
In this paper,the main research work and related reports of materials science research in China’s space technology field during 2020-2022 are summarized.This paper covers Materials Sciences in Space Environment,Mater...In this paper,the main research work and related reports of materials science research in China’s space technology field during 2020-2022 are summarized.This paper covers Materials Sciences in Space Environment,Materials Sciences for Space Environment,Materials Behavior in Space Environment and Space experimental hardware for material investigation.With the rapid development of China’s space industry,more scientists will be involved in materials science,space technology and earth science researches.In the future,a series of disciplines such as space science,machinery,artificial intelligence,digital twin and big data will be further integrated with materials science,and space materials will also usher in new development opportunities.展开更多
It has been documented that a cyclic three-neuron-based neural network with resistive synaptic weights cannot exhibit chaos.Towards this end,a memristive cyclic three-neuron-based neural network is presented using a m...It has been documented that a cyclic three-neuron-based neural network with resistive synaptic weights cannot exhibit chaos.Towards this end,a memristive cyclic three-neuron-based neural network is presented using a memristive weight to substitute a resistive weight.The memristive cyclic neural network always has five equilibrium points within the parameters of interest,and their stability analysis shows that they are one index-2 saddle-focus,two index-1 saddle-foci,and two stable node-foci,respectively.Dynamical analyses are performed for the memristive cyclic neural network by several numerical simulation methods.The results demonstrate that the memristor synapse-based neural network with the simplest cyclic connection can not only exhibit chaos,but also present global coexisting attractors composed of stable points and unstable periodic or chaotic orbits under different initial conditions.Besides,with the designed implementation circuit,Multisim circuit simulations and hardware experiments are executed to validate the numerical simulations.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.51777016 and 61801054)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20191451)。
文摘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.
基金Supported by the National Natural Science Fundation of China(51873146)。
文摘In this paper,the main research work and related reports of materials science research in China’s space technology field during 2020-2022 are summarized.This paper covers Materials Sciences in Space Environment,Materials Sciences for Space Environment,Materials Behavior in Space Environment and Space experimental hardware for material investigation.With the rapid development of China’s space industry,more scientists will be involved in materials science,space technology and earth science researches.In the future,a series of disciplines such as space science,machinery,artificial intelligence,digital twin and big data will be further integrated with materials science,and space materials will also usher in new development opportunities.
基金supported by the National Natural Science Foundation of China(Grant Nos.62201094,62271088 and 12172066)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20210850)+1 种基金the Scientific Research Foundation of Jiangsu Provincial Education Department,China(Grant No.22KJB510001)。
文摘It has been documented that a cyclic three-neuron-based neural network with resistive synaptic weights cannot exhibit chaos.Towards this end,a memristive cyclic three-neuron-based neural network is presented using a memristive weight to substitute a resistive weight.The memristive cyclic neural network always has five equilibrium points within the parameters of interest,and their stability analysis shows that they are one index-2 saddle-focus,two index-1 saddle-foci,and two stable node-foci,respectively.Dynamical analyses are performed for the memristive cyclic neural network by several numerical simulation methods.The results demonstrate that the memristor synapse-based neural network with the simplest cyclic connection can not only exhibit chaos,but also present global coexisting attractors composed of stable points and unstable periodic or chaotic orbits under different initial conditions.Besides,with the designed implementation circuit,Multisim circuit simulations and hardware experiments are executed to validate the numerical simulations.
