The event-based vision sensor(EVS),which can generate efficient spiking data streams by exclusively detecting motion,exemplifies neuromorphic vision methodologies.Generally,its inherent lack of texture features limits...The event-based vision sensor(EVS),which can generate efficient spiking data streams by exclusively detecting motion,exemplifies neuromorphic vision methodologies.Generally,its inherent lack of texture features limits effectiveness in complex vision processing tasks,necessitating supplementary visual information.However,to date,no event-based hybrid vision solution has been developed that preserves the characteristics of complete spike data streams to support synchronous computation architectures based on spiking neural network(SNN).In this paper,we present a novel spike-based sensor with digitized pixels,which integrates the event detection structure with the pulse frequency modulation(PFM)circuit.This design enables the simultaneous output of spiking data that encodes both temporal changes and texture information.Fabricated in 180 nm process,the proposed sensor achieves a resolution of 128×128,a maximum event rate of 960 Meps,a grayscale frame rate of 117.1 kfps,and a measured power consumption of 60.1 mW,which is suited for high-speed,low-latency,edge SNNbased vision computing systems.展开更多
构建的两种适用于谐振时钟的CMOS触发器结构:SAER(Sense Amplifier Energy Re-covery)和SDER(Static Differential Energy Recovery),克服了传统触发器在谐振时钟触发下短路功耗大的问题,适用于对时钟网络实现能量回收与节省的系统。在S...构建的两种适用于谐振时钟的CMOS触发器结构:SAER(Sense Amplifier Energy Re-covery)和SDER(Static Differential Energy Recovery),克服了传统触发器在谐振时钟触发下短路功耗大的问题,适用于对时钟网络实现能量回收与节省的系统。在SMIC 0.13μm工艺下进行功耗和时序参数仿真,对比应用在同样谐振时钟下的传统主从结构触发器MSDFF(Master-Slave DFlip-flop)和高性能触发器HLFF(Hybrid Latch Flip-flop),SAER在测试的频率范围内保证高性能时序参数的同时,实现了三分之一以上的功耗节省。展开更多
基金supported in part by the National Key Research and Development Program of China(Grant No.2022YFB2804401)the National Natural Science Foundation of China(Grant Nos.62334008,62134004,62404218)+1 种基金the Beijing Natural Science Foundation(Grant No.Z220005)Chinese Academy of Sciences(Grant No.ZDBS-LY-JSC008).
文摘The event-based vision sensor(EVS),which can generate efficient spiking data streams by exclusively detecting motion,exemplifies neuromorphic vision methodologies.Generally,its inherent lack of texture features limits effectiveness in complex vision processing tasks,necessitating supplementary visual information.However,to date,no event-based hybrid vision solution has been developed that preserves the characteristics of complete spike data streams to support synchronous computation architectures based on spiking neural network(SNN).In this paper,we present a novel spike-based sensor with digitized pixels,which integrates the event detection structure with the pulse frequency modulation(PFM)circuit.This design enables the simultaneous output of spiking data that encodes both temporal changes and texture information.Fabricated in 180 nm process,the proposed sensor achieves a resolution of 128×128,a maximum event rate of 960 Meps,a grayscale frame rate of 117.1 kfps,and a measured power consumption of 60.1 mW,which is suited for high-speed,low-latency,edge SNNbased vision computing systems.
