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CMOS mixed-signal spiking neural network circuit using a time-domain digital-to-analog converter

机译:CMOS混合信号尖刺神经网络电路使用时域数模转换器

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This paper proposes a high energy efficiency CMOS mixed-signal spiking neural network circuit using a time-domain digital-to-analog converter (TDAC) for realizing online and on-chip brainmorphic learning hardware. The circuit consists of a mixed-signal synapse circuit and an analog leaky integrate-and-fire neuron circuit. The TDAC converts synaptic weights held by digital memory into an analog current that realizes a biologically plausible synaptic response, which is employed as an output stage for our synapse circuit. To evaluate online and on-chip learning operation, the remote supervised method (ReSuMe) was implemented using TSMC 40-nm (1-poly, 8-metal) CMOS technology, and this circuit was evaluated by a Spectre circuit simulator. The circuit simulation results show that energy per synaptic event in our circuit was 20.1 fJ for multiply-accumulation operation and 92.1 fJ for ReSuMe.
机译:本文提出了一种使用时域数模转换器(TDAC)的高能量效率CMOS混合信号尖刺神经网络电路,用于实现在线和片上大脑术学习硬件。 电路由混合信号突触电路和模拟泄漏集成和灭火神经元电路组成。 TDAC将数字存储器保持的突触权重转换为实现生物合理的突触响应的模拟电流,该突触响应被用作我们的Synapse电路的输出级。 为了评估在线和片上学习操作,使用TSMC 40-NM(1-Poly,8-METAL)CMOS技术实现远程监控方法(简历),并且该电路由幽灵电路模拟器评估。 电路仿真结果表明,电路中每个突触事件的能量为20.1 fj,用于乘法累积操作和92.1 fj用于恢复。

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