用于神经网络的Ga-Sn-O薄膜的研究与开发

Keisuke Ikushima, J. Shimura, T. Matsuda, M. Kimura, H. Yamane, Y. Nakashima
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引用次数: 0

摘要

神经网络是一种基于人脑的信息处理模型,人们对其进行了大量的研究。然而,为了实现神经网络的硬件,必须实现高集成度。在这项研究中,我们使用Ga-Sn-O (GTO)薄膜(一种不含稀有金属的非晶氧化物半导体)制造神经网络突触。该突触为平面型,具有适用于改进的Hebb学习规则的退化特征。我们利用这一结果在LSI表面沉积了GTO薄膜。将LSI视为一个神经元,可以满足突触与神经元之间的关系,从而可以构造一个简单的神经网络。最后,我们利用它成功进行了汉字学习实验
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Research and development of Ga-Sn-O thin films for application to neural networks
Neural networks are information processing models based on the human brain, and they have been activity studied. However, in order to realize the hardware of the neural network, it is necessary to achieve high integration. In this study, we fabricated synapses for neural networks using the Ga-Sn-O (GTO) thin films, which is rare-metal-free amorphous oxide semiconductor. This synapse was a planar type and found to have degradation characteristics applicable to modified Hebb's learning rule. We used this result to deposit the GTO thin film on LSI surface. By considering the LSI as a neuron, it was possible to satisfy the relation between the synapse and the neuron, and as a result, a simple neural network could be constructed. Finally, we succeeded in character learning experiment using it
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