为解决传统电平交叉模数转换器(LC ADC)精度较低和噪声整形逐次逼近寄存器(NS SAR)ADC功耗较大的问题,提出了一种应用于移动物联网(IoT)随机稀疏信号采集的LC-NS SAR ADC。在NS SAR ADC前端插入8 bit的LC ADC作为输入信号活跃度的预检...为解决传统电平交叉模数转换器(LC ADC)精度较低和噪声整形逐次逼近寄存器(NS SAR)ADC功耗较大的问题,提出了一种应用于移动物联网(IoT)随机稀疏信号采集的LC-NS SAR ADC。在NS SAR ADC前端插入8 bit的LC ADC作为输入信号活跃度的预检测电路,在电平交叉发生后开启NS SAR ADC的转换。二阶无源噪声整形电路积分过程只在事件触发后发生,从而能够根据输入信号的活跃度动态调节整体功耗。在1.8 V 180 nm CMOS工艺、采样率为40 kS/s、过采样率(OSR)为20、带宽为1 kHz下对该ADC进行仿真验证,结果表明信噪失真比(SNDR)达到87 dB,电路功耗为2.70μW,心电图信号输入时功耗仅为0.79μW,相较于传统等间隔奈奎斯特采样ADC,采样点减少了73%,在处理生物医学信号时实现了约5∶1的数据压缩比,Schreier品质因数(FoMs)和Walden品质因数(FoMw)分别为172.6 dB和67.0 fJ/conv.step。展开更多
The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases...The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases with high volume fractions where there are collisions between multiple objects.EDM simulations are suited for cases with low volume fractions from the viewpoint of CPU time.A method combining EDM and TDM called Hybrid Algorithm of event-driven and time-driven methods(HAET)is presented in this paper.The HAET method employs TDM for the areas with high volume fractions and EDM for the remaining areas with low volume fractions.It can decrease the CPU time for simulating granular flows with strongly non-uniform volume fractions.In addition,a modified EDM algorithm using a constant time as the lower time step limit is presented.Finally,an example is presented to demonstrate the hybrid algorithm.展开更多
文摘为解决传统电平交叉模数转换器(LC ADC)精度较低和噪声整形逐次逼近寄存器(NS SAR)ADC功耗较大的问题,提出了一种应用于移动物联网(IoT)随机稀疏信号采集的LC-NS SAR ADC。在NS SAR ADC前端插入8 bit的LC ADC作为输入信号活跃度的预检测电路,在电平交叉发生后开启NS SAR ADC的转换。二阶无源噪声整形电路积分过程只在事件触发后发生,从而能够根据输入信号的活跃度动态调节整体功耗。在1.8 V 180 nm CMOS工艺、采样率为40 kS/s、过采样率(OSR)为20、带宽为1 kHz下对该ADC进行仿真验证,结果表明信噪失真比(SNDR)达到87 dB,电路功耗为2.70μW,心电图信号输入时功耗仅为0.79μW,相较于传统等间隔奈奎斯特采样ADC,采样点减少了73%,在处理生物医学信号时实现了约5∶1的数据压缩比,Schreier品质因数(FoMs)和Walden品质因数(FoMw)分别为172.6 dB和67.0 fJ/conv.step。
基金supported by a grant from Department of Energy and Process Engineering,Norwegian University of Science and Technology,Institute for Energy Technology(IFE)and SINTEF through the FACE(Multiphase Flow Assurance Innovation Center)project.
文摘The classical discrete element approach(DEM)based on Newtonian dynamics can be divided into two major groups,event-driven methods(EDM)and timedriven methods(TDM).Generally speaking,TDM simulations are suited for cases with high volume fractions where there are collisions between multiple objects.EDM simulations are suited for cases with low volume fractions from the viewpoint of CPU time.A method combining EDM and TDM called Hybrid Algorithm of event-driven and time-driven methods(HAET)is presented in this paper.The HAET method employs TDM for the areas with high volume fractions and EDM for the remaining areas with low volume fractions.It can decrease the CPU time for simulating granular flows with strongly non-uniform volume fractions.In addition,a modified EDM algorithm using a constant time as the lower time step limit is presented.Finally,an example is presented to demonstrate the hybrid algorithm.
