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Evaluation of Letter Reproduction System Using Cellular Neural Network and Oxide Semiconductor Synapses by Logic Simulation

机译:基于神经网络和氧化物半导体突触的字母再现系统逻辑仿真评估

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A letter reproduction system has been developed by a cellular neural network and oxide semiconductor synapses and evaluated by logic simulation. A cellular neural network is utilized because it is suitable for large-scale integration of electronic devices, and oxide semiconductor devices are utilized as synapse elements because the characteristic deterioration can be employed as strength plasticity of synaptic connection with modified Hebbian learning. In this article, first, the structure and operation of the letter reproduction system are explained. Next, it is evaluated by logic simulation, where the dependence of the correction accuracy of the letter reproduction on the variation of deterioration rate of the oxide semiconductor synapses is analyzed.
机译:字母再现系统已经通过细胞神经网络和氧化物半导体突触进行了开发,并通过逻辑仿真进行了评估。利用了细胞神经网络,因为它适合于电子设备的大规模集成,并且氧化物半导体器件被用作突触元件,因为特性劣化可以被用作具有改进的希伯来学习的突触连接的强度可塑性。在本文中,首先,说明字母再现系统的结构和操作。接下来,通过逻辑仿真进行评估,其中分析字母再现的校正精度对氧化物半导体突触的劣化率的变化的依赖性。

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