Driven by exponential growth of computing power demand,the miniaturization of tran-sistor density in computer chips is approaching the physical limit,and the traditional Von Neumann com-puting architecture,which separates storage and computing,has formed speed and power bottlenecks.A promising alternative scheme is brain-like computing based on memristor neuromorphic dynamics.Mem-ristors can imitate the behaviors of neurons and synapses to directly process and store information at the physical level,achieving a new brain-like computing architecture with high energy efficiency,high compu-ting power and in-memory computing.In this review paper,the latest progress in the study on neuromor-phic dynamics of local active memristors is mainly introduced,including the characteristics and modeling of locally active memristors,artificial neuron models and design methods based on edge of chaos theory and locally active memristors,dynamic mechanisms of memristor-based neuron action potentials,theoret-ical explanations of the Smale paradox and the Chimera state in memristive neural networks,as well as the physical implementations and experiments of memristor-based neurons.
memristorlocal activityedge of chaosneuronbrain-like computing
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