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A mixed-signal universal neuromorphic computing system

机译:混合信号通用神经形态计算系统

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Neuromorphic information processing systems offer the potential to overcome imminent problems of state-of-the-art computers, in particular the energy efficiency problem, the device reliability problem and the software complexity problem. This paper starts with a short overview of state-of-the-art neuromorphic hardware implementations and their applications. It then describes the time-accelerated mixed-signal approach of the BrainScaleS project in some detail.
机译:神经形态信息处理系统提供了克服现有计算机迫在眉睫的问题的潜力,尤其是能效问题,设备可靠性问题和软件复杂性问题。本文首先简要介绍了最新的神经形态硬件实现及其应用。然后,它详细描述了BrainScaleS项目的时间加速混合信号方法。

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