以IGZO薄膜为突触,LSI为神经元的细胞神经网络

D. Yamakawa, Yuki Shibayama, H. Yamane, Y. Nakashima, M. Kimura
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引用次数: 0

摘要

人工神经网络是人脑的信息处理模型。特别是硬件神经网络具有鲁棒性、并行分布式处理、低功耗等特点。我们认为硬件神经网络优于软件神经网络。然而,硬件神经网络需要高集成度。因此,我们提出了一种使用LSI和IGZO薄膜的神经网络。我们用电流值作为突触结合强度。发现使用IGZO薄膜的突触电流值随着时间的增加而逐渐降低。神经网络在字母识别方面取得了成功。
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Cellular Neural Network using IGZO Thin Film as Synapses and LSI as Neurons
Artificial neural networks are infomation processing models of human brains. Especially, hardware neural networks have functions such as robustness, parallel distributed processing, and low power consumption. We think hardware neural networks are superior to software neural networks. However, hardware neural networks need high integration. Therefore, we propose a neural network using a LSI and IGZO thin films. We used current value as the synaptic bond strength. It is found that current value of synapses using IGZO thin films gradually decreased as time gose by. The neural networks succeeded in letter recgnition.
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