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Impact of Selector Devices in Analog RRAM-Based Crossbar Arrays for Inference and Training of Neuromorphic System

机译:选择器设备在基于模拟RRAM的交叉开关阵列中对神经形态系统的推理和训练的影响

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The impact of selector devices on the inference and training accuracy of a resistive random access memory (RRAM)-based neuromorphic computing system is rarely studied. In this paper, we analyze the weighted sum and weight update functions in a one-selecto
机译:很少研究选择器设备对基于电阻式随机存取存储器(RRAM)的神经形态计算系统的推理和训练精度的影响。在本文中,我们以单选方式分析了加权和和权重更新函数

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