一个老化的弹性神经网络架构

2018 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH) Pub Date : 2018-07-17 DOI:10.1145/3232195.3232208

S. Mozaffari, K. Gnawali, S. Tragoudas

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引用次数: 8

摘要

最近的人工神经网络架构使用忆阻器来存储突触权值。由于记忆电阻器结构致密，且具有极高的平行度，因此采用了交叉杆结构。晶体管老化影响其计算精度。介绍了一种基于忆阻器的神经网络结构的改进，采用内置的基于电流的校准电路。实验结果表明，该方法能有效缓解细胞老化效应。

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An Aging Resilient Neural Network Architecture

Recent artificial neural network architectures use memristors to store synaptic weights. The crossbar structure of memristors is used because of its dense structure and extreme parallelism. Transistor aging impacts their computational accuracy. An enhancement of the memristor-based neural network architecture is introduced using built-in current-based calibration circuit. It is shown experimentally that the proposed approach alleviates the cell aging effect.

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2018 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH)

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