可配置聚合物导线突触装置的启发式模型

IF 0.5 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Yoshiki Amemiya, A. José, Naruki Hagiwara, M. Akai‐Kasaya, T. Asai
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引用次数: 0

摘要

:近年来,人工智能(AI)的非易失性模拟器件得到了大量研究;然而,它侧重于全耦合神经网络。相比之下,聚合物线型突触装置已经被提出并证明,它可以像生物神经网络一样任意连接。在本研究中,我们基于先前的研究结果对聚合物线突触装置进行了建模,并演示了一个将简单感知器(AI)应用于该模型的示例。我们的研究结果表明,有可能预测在人工智能中使用聚合物丝突触元件的有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Heuristic model for configurable polymer wire synaptic devices
: Recently, there has been considerable research on nonvolatile analog devices for artificial intelligence (AI); however, it focuses on all-coupled neural networks. In contrast, polymer wire-type synaptic devices, which can be expected to be arbitrarily wired similar to a biological neural network, have already been proposed and demonstrated. In this study, we model a polymer wire synaptic device based on the results of previous research, and demonstrate an example of applying simple perceptron (AI) to the model. The results of our study show that it is possible to predict effective methods of using polymer wire synaptic elements in AI.
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来源期刊
IEICE Nonlinear Theory and Its Applications
IEICE Nonlinear Theory and Its Applications MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
自引率
20.00%
发文量
67
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