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A neuromorphic core based on threshold switching memristor with asynchronous address event representation circuits

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Science China(Information Sciences) 2022年第2期65卷 211-217页

作者： Jinsong WEI Jilin ZHANG Xumeng ZHANG Zuheng WU Rui WANG Jian LU Tuo SHI Mansun CHAN Qi LIU Hong CHEN School of Microelectronics University of Science and Technology of China Institute of Microelectronics of Chinese Academy of Sciences Zhejiang Lab Department of Microelectronics and Nanoelectronics Tsinghua University Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology

The full memristive network hardware features high density and excellent scalability. However,recent researches on the full memristive network have been limited to a single-layer network, due to the lack of effective and flexible communication between neurons. In this design, we demonstrate a neuromorphic core based on Ag/Si O2/Au threshold switching memristor, which has built-in asynchronous address event representation(AER) circuits to provide flexible communication between neurons. Since temporally sparse spikes are the medium of communication between neurons, the AER circuits are designed to transmit spikes serially which have been encoded with neurons’ addresses before transmission. With the asynchronous circuits design, the AER circuits will detect neurons’ output in real-time. To test the performance of the neuromorphic core, we designed a behavioral simulator for the neuromporphic core to simulate the liquid state machine(LSM) network, which achieves a 100% recognition rate in the free spoken digital dataset. The simulation results show that the neuromorphic core obtains 35 times higher performance than the CPU and111 times higher energy efficiency than the GPU.

关键词： leaky-integration-and-fire (LIF) memristor threshold switching artificial neuron AER circuits asynchronous circuits on-chip communication

Voltage-controllable magnetic skyrmion dynamics for spiking neuron device applications

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Chinese Physics B 2022年第1期31卷 664-668页

作者：朱明敏崔淑婷徐晓飞施胜宾年迪青罗京邱阳杨浛郁国良周浩淼 Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province College of Information EngineeringChina Jiliang UniversityHangzhou 310018China

Voltage-controlled magnetic skyrmions have attracted special attention because they satisfy the requirements for well-controlled high-efficiency and energy saving for future skyrmion-based neuron device *** this work,we propose a compact leaky-integrate-fire(LIF)spiking neuron device by using the voltage-driven skyrmion dynamics in a multiferroic nanodisk *** skyrmion dynamics is controlled by well tailoring voltage-induced piezostrains,where the skyrmion radius can be effectively modulated by applying the piezostrain *** the biological neuron,the proposed skyrmionic neuron will accumulate a membrane potential as skyrmion radius is varied by inputting the continuous piezostrain spikes,and the skyrmion radius will return to the initial state in the absence of ***,this skyrmion radius-based membrane potential will reach a definite threshold value by the strain stimuli and then reset by removing the *** the LIF neuronal functionality and the behaviors of the proposed skyrmionic neuron device are elucidated through the micromagnetic simulation *** results may benefit the utilization of skyrmionic neuron for constructing the future energy-efficient and voltage-tunable spiking neural networks.

关键词： magnetic skyrmion leaky-integrate-fire multiferroic heterostructure artificial neuron

Memristive dynamics enabled neuromorphic computing systems

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Science China(Information Sciences) 2023年第10期66卷 5-19页

作者： Bonan YAN Yuchao YANG Ru HUANG Center for Brain Inspired Chips Institute for Artificial Intelligence Peking University Beijing Advanced Innovation Center for Integrated Circuits School of Integrated Circuits Peking University School of Electronic and Computer Engineering Peking University Center for Brain Inspired Intelligence Chinese Institute for Brain Research(CIBR)

The slowing down of transistor scaling and explosive growth for intelligence computing power emerge as the two driving factors for the study of novel devices and materials to pursue highly-efficient computing systems. Memristors, incorporating rich intrinsic dynamics, are a promising candidate for constructing efficient and scalable bio-inspired computing systems. In this progress report, we review the latest advances in novel types of memristors as well as their applications in implementing neuromorphic computing systems. This paper not only covers the memristive dynamics-enabled bionic computing systems but also discusses the memristive sensory systems that integrate sensing and computing. Eventually, device-circuit co-optimization methods are given to emphasize the trend of cross-layer co-design in this fast-evolving *** innovation in memristor devices mainly focuses on specialized computing hardware and yields superior computing and sensing efficiency. At last, we offer our insight into the trend of state-of-the-art research in memristive materials, devices, circuits, and systems.

关键词： memrsitor memristive dynamics artificial synapse artificial neuron neuromorphic computing

Spin torque oscillator based on magnetic tunnel junction with MgO cap layer for radio-frequency-oriented neuromorphic computing

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中国物理B:英文版 2023年第10期32卷 656-659页

作者：涂华垚雒雁翔曾柯心吴宇轩张黎可张宝顺曾中明 School of Nano Technology and Nano Bionics University of Science and Technology of ChinaHefei 230026China Nanofabrication Facility Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China School of Electronics and Information Engineering Wuxi UniversityWuxi 214105China Nanchang(SINANONC)Nano-Devices and Technologies Division Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesNanchang 330200China Nano Science and Technology Institute University of Science and Technology of ChinaSuzhou 215123China

Recently,it has been proposed that spin torque oscillators(STOs)and spin torque diodes could be used as artificial neurons and synapses to directly process microwave signals,which could lower latency and power consumption ***,one critical challenge is to make the microwave emission frequency of the STO stay constant with a varying input *** this work,we study the microwave emission characteristics of STOs based on magnetic tunnel junction with MgO cap *** applying a small magnetic field,we realize the invariability of the microwave emission frequency of the STO,making it qualified to act as artificial ***,we have simulated an artificial neural network using STO neuron to recognize the handwritten digits in the Mixed National Institute of Standards and Technology database,and obtained a high accuracy of 92.28%.Our work paves the way for the development of radio-frequency-oriented neuromorphic computing systems.

关键词： spin torque oscillators artificial neuron neuromorphic computing magnetic tunnel junctions

Triboelectric nanogenerator for neuromorphic electronics

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能源评论(英文) 2023年第1期2卷 16-30页

作者： Guanglong Ding Su-Ting Han Vellaisamy A.L.Roy Chi-Ching Kuo Ye Zhou Institute for Advanced Study Shenzhen UniversityShenzhen518060PR China College of Electronics and Information Engineering Shenzhen518060PR China James Watt School of Engineering University of GlasgowGlasgowG128QQUK Institute of Organic and Polymeric Materials Research and Development Center of Smart Textile TechnologyNational Taipei University of TechnologyTaipei10608TaiwanChina

Building the brain-inspired neural network computing system based neuromorphic electronics is an effective approach to break the von Neumann bottleneck on the hardware level and realize the information processing with high efficiency and low energy consumption in this big data explosion *** nanogenerator(TENG)has two functions of sensing and energy conversion,which promote the application as sensor and/or power supply in self-powered neuromorphic electronics for data storage and biological synapse/neuron behaviors *** article highlights the relevant works of TENGs for memory devices,artificial synapses and artificial neurons,performs a systematic comparison,and puts forward the future research possibilities and challenges,with the hope of attracting more researchers into this field and promoting the development of TENG based neuromorphic electronics.

关键词： Triboelectric nanogenerator Neuromorphic electronic Memory artificial synapse artificial neuron Tactile perception system

Application of pH Control based on Adaptive PID in Acid-alkali Neutralization Reaction

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Application of pH Control based on Adaptive PID in Acid-alka...

Data Fusion Method for Manufacturing Measurement

第三十一届中国控制会议

作者： YANG Youlin~1 WU Qinghui~2 DING Shuo~2 1.College of Engineering Bohai University Jinzhou 121013 China 2.College of Engineering Bohai University Jinzhou 121013 China

＜正＞An adaptive PID controller based on artificial neuron is designed to improve the interference immunity of pH system in acid-alkali *** using the learning algorithm of artificial neuron,parameter self-tuning and adaptability are realized in the control,which solves the problems of long adjustment time,large overshoot and poor anti-interference of PID control in acid-alkali *** results show that the adaptive PID controller has shorter repose time and stronger robustness compared with conventional PID controller.

关键词： Adaptive PID artificial neuron pH control neutralization reaction

来源： cnki会议评论

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厦门大学学报（自然科学版） 2002年第S1期41卷 266-页

作者： GU Li-chen, ZHANG You-yun, QUO Da-mou (School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

A data fusion method of online multisensors is prop os ed in this paper based on artificial neuron. First, the dynamic data fusion mode l on artificial neuron is built. Then the calibration of data fusion is discusse d with self-adaptive weighing technique. Finally performance of the method is d emonstrated by an online vibration measurement case. The results show that the f used data are more stable, sensitive, accurate, reliable than that of single sen sor data.

关键词： multisensor measures artificial neuron data fus ion fusion system calibration