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Study on simplification of processing elements in neural networks using circuit simulation

机译:利用电路仿真简化神经网络中处理元素的研究

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We are developing cellular neural networks using thin-film transistors (TFTs). Although simplification of the processing elements such as neurons and synapses is also needed for the cellular neural network, it is difficult and time-consuming to fabricate and evaluate actual devices. Therefore, we are studying the simplification of the processing elements in the neural networks by using circuit simulation. We confirmed that the neuron can be realized only using a 2-inverter and 2 switch circuit, and the synapse can be realized only using a resister. These results indicate a future possibility for ultra-large scale integrated brain chips for artificial intelligences.
机译:我们正在开发使用薄膜晶体管(TFT)的细胞神经网络。尽管对于细胞神经网络也需要简化诸如神经元和突触之类的处理元件,但是制造和评估实际的设备是困难且耗时的。因此,我们正在研究通过使用电路仿真来简化神经网络中的处理元素。我们确认,仅使用2反相器和2开关电路就可以实现神经元,而仅使用电阻器就可以实现突触。这些结果表明,用于人工智能的超大规模集成脑芯片的未来可能性。

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