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Memristive Artificial Synapses for Neuromorphic Computing

机译:神经形态计算的椎间膜人工突触

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Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the von Neumann architecture.This computing is realized based on memristive hardware neural networks in which synaptic devices that mimic biological synapses of the brain are the primary units.Mimicking synaptic functions with these devices is critical in neuromorphic systems.In the last decade,electrical and optical signals have been incorporated into the synaptic devices and promoted the simulation of various synaptic functions.In this review,these devices are discussed by categorizing them into electrically stimulated,optically stimulated,and photoelectric synergetic synaptic devices based on stimulation of electrical and optical signals.The working mechanisms of the devices are analyzed in detail.This is followed by a discussion of the progress in mimicking synaptic functions.In addition,existing application scenarios of various synaptic devices are outlined.Furthermore,the performances and future development of the synaptic devices that could be significant for building efficient neuromorphic systems are prospected.
机译:神经形态计算模拟生物脑功能的操作,以便信息处理可以解决von Neumann架构的瓶颈。基于Memristive硬件神经网络实现了哪种计算,其中大脑的模仿生物突触的突触装置是主要单元。模仿与这些设备的突触功能在神经系统中至关重要。在过去的十年中,电气和光学信号已经结合到突触装置中并促进了各种突触函数的模拟。在此综述中,通过将它们进行分类来讨论这些设备。基于电气和光学信号的刺激刺激,光学刺激和光电协同突触装置。详细分析了设备的工作机制。然后讨论了模拟突触函数的进展。此外,现有的应用方案各种突触概述了设备的概述。展望可能对构建有效的神经形式系统有重大的突触装置的突触装置的性能和未来发展是展望的。

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