论文标题
用于尖峰神经网络硬件的时域数字到纳阿尔格转换器
Time-domain digital-to-analog converter for spiking neural network hardware
论文作者
论文摘要
我们提出了一个新的数字转换器转换器（DAC），用于实现混合信号尖峰神经网络的突触电路。我们将此电路命名为“ Time域DAC（TDAC）”。这产生了使用一个电流波形将数字输入代码转换为电压的权重。因此，TDAC比包括许多当前来源和电阻的传统DAC更紧凑。此外，具有泄漏阻力的TDAC再现了以α函数或双指数方程表示的生物合理的突触反应。我们将显示由TSMC 40 nm CMOS过程设计的TDAC和电路模拟结果的数值分析结果。
We propose a new digital-to-analog converter (DAC) for realizing a synapse circuit of mixed-signal spiking neural networks. We named this circuit "time-domain DAC (TDAC)". This produces weights for converting a digital input code into voltage using one current waveform. Therefore, a TDAC is more compact than a conventional DAC that comprises many current sources and resistors. Moreover, a TDAC with leak resistance reproduces biological plausible synaptic responses that are expressed as alpha functions or dual exponential equations. We will show numerical analysis results of a TDAC and circuit simulation results of a circuit designed by the TSMC 40 nm CMOS process.
