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arXiv 2023年

作者： Li, Yi Wang, Songqi Zhao, Yaping Wang, Shaocong Zhang, Woyu He, Yangu Lin, Ning Cui, Binbin Chen, Xi Zhang, Shiming Jiang, Hao Lin, Peng Zhang, Xumeng Qi, Xiaojuan Wang, Zhongrui Xu, Xiaoxin Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong State Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Frontier Institute of Chip and System Fudan University Shanghai200433 China College of Computer Science and Technology Zhejiang University Zhejiang310027 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong University of Chinese Academy of Sciences Beijing100049 China Institute of Mind The University of Hong Kong Hong Kong

The rapid advancement of artificial intelligence (AI) has been marked by the large language models exhibiting human-like intelligence. However, these models also present unprecedented challenges to energy consumption and environmental sustainability, which are exacerbated by the increasing number of users and the development of even larger models. One promising solution is to revisit analogue computing, a technique that predates digital computing and exploits emerging analogue electronic devices, such as resistive memory, which features in-memory computing, high scalability, and nonvolatility that addresses the von Neumann bottleneck, slowdown of Moore’s law, and volatile DRAM of conventional digital hardware. However, analogue computing still faces the same challenges as before: programming nonidealities and expensive programming due to the underlying devices physics. Therefore, leveraging the efficiency advantage while mitigating the programming disadvantage of analogue computing with resistive memory is a major open problem in AI hardware and electronics communities. Here, we report a universal solution, software-hardware co-design using structural plasticity-inspired edge pruning to optimize the topology of a randomly weighted analogue resistive memory neural network. Software-wise, the topology of a randomly weighted neural network is optimized by pruning connections rather than precisely tuning resistive memory weights. Hardware-wise, we reveal the physical origin of the programming stochasticity using transmission electron microscopy, which is leveraged for large-scale and low-cost implementation of an overparameterized random neural network containing high-performance sub-networks. We implemented the co-design on a 40nm 256K resistive memory macro, observing 17.3% and 19.9% accuracy improvements in image and audio classification on FashionMNIST and Spoken digits datasets, as well as 9.8% (2%) improvement in PR (ROC) in image segmentation on DRIVE datasets, r

关键词： Energy utilization

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Continuous-time digital twin with analog memristive neural ordinary differential equation solver

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Science advances 2025年第22期11卷 eadr7571页

作者： Hegan Chen Jichang Yang Jia Chen Songqi Wang Shaocong Wang Dingchen Wang Xinyu Tian Yifei Yu Xi Chen Yinan Lin Qifan Zhu Yangu He Xiaoshan Wu Yi Li Xinyuan Zhang Ning Lin Meng Xu Xumeng Zhang Xiaojuan Qi Zhongrui Wang Han Wang Dashan Shang Qi Liu Kwang-Ting Cheng Ming Liu Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong China. School of Microelectronics Southern University of Science and Technology Shenzhen 518055 China. Center for Advanced Semiconductors and Integrated Circuits the University of Hong Kong Hong Kong China. Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong China. School of Integrated Circuits Hubei Key Laboratory for Advanced Memories Huazhong University of Science and Technology Wuhan 430074 China. State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai 200433 China. State Key Lab of Fabrication Technologies for Integrated Circuits and Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing 100029 China. University of Chinese Academy of Sciences Beijing 100049 China.

Digital twins, which replicate real-world entities through computational models, are transforming manufacturing and automation. While recent advances in machine learning have enabled data-driven digital twin development using discrete-time data and finite-depth models on digital hardware, these approaches face significant limitations. They struggle to capture continuous-time dynamics and model complex systems, and suffer from substantial time and energy overheads due to physically separated storage and processing as well as frequent analog-digital (A/D) conversions. Here, we propose a memristive neural ordinary differential equation (ODE) solver for digital twins. Our approach is intrinsically time-continuous using infinite-depth neural networks to model complex dynamics. Fully analog memristor arrays collocate storage and computation, addressing the von Neumann bottleneck and reducing A/D conversion requirements. We experimentally validate our solver on digital twins of HP variable-resistor model and Lorenz96 dynamics, demonstrating a 166.5-fold/369.3-fold speedup and a 499.0-fold/673.9-fold improvement in energy efficiency, respectively. This work paves the way to future digital twins for Industry 4.0.

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Tellurium nanowire retinal nanoprosthesis improves vision in models of blindness

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Science 2025年第6751期388卷

作者： Shuiyuan Wang Chengyong Jiang Yiye Yu Zhenhan Zhang Ruge Quhe Ruyi Yang Yufei Tian Xindong Chen Wenqiang Fan Yinge Niu Biao Yan Chunhui Jiang Yang Wang Zhen Wang Chunsen Liu Weida Hu Jiayi Zhang Peng Zhou State Key Laboratory of Integrated Chips and Systems (SKLICS) College of Integrated Circuits and Micro-Nano Electronics School of Microelectronics State Key Laboratory of Brain Function and Disorders MOE Frontiers Center for Brain Science Institutes of Brain Science Department of Ophthalmology and Vision Science Eye and ENT Hospital Fudan University Shanghai China. Shaoxin Laboratory Shaoxing Zhejiang China. State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai China. School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore. State Key Laboratory of Information Photonics and Optical Communications and School of Science Beijing University of Posts and Telecommunications Beijing China.

Present vision restoration technologies have substantial constraints that limit their application in the clinical setting. In this work, we fabricated a subretinal nanoprosthesis using tellurium nanowire networks (TeNWNs) that converts light of both the visible and near-infrared–II spectra into electrical signals. The broad-spectrum coverage is made possible by a combination of narrow bandgaps, strong absorption, and engineered asymmetries. Implanted into blind mice, the TeNWNs restored pupillary reflexes and enabled visually cued learning under visible and near-infrared 1550-nanometer light. In nonhuman primates, TeNWNs elicited robust retina-derived neural responses, confirming biocompatibility and feasibility. By restoring lost photosensitivity and extending vision to near-infrared, this nanoprosthesis offers a promising approach for restoring vision.

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JUNO sensitivity on proton decay p→νK^(+)searches

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Chinese Physics C 2023年第11期47卷 7-22页

作者： Angel Abusleme Thomas Adam Shakeel Ahmad Rizwan Ahmed Sebastiano Aiello Muhammad Akram 安丰鹏安琪 Giuseppe Andronico Nikolay Anfimov Vito Antonelli Tatiana Antoshkina Burin Asavapibhop João Pedro Athayde Marcondes de André Didier Auguste Nikita Balashov Wander Baldini Andrea Barresi Davide Basilico Eric Baussan Marco Bellato Antonio Bergnoli Thilo Birkenfeld Sylvie Blin David Blum Simon Blyth Anastasia Bolshakova Mathieu Bongrand Clément Bordereau Dominique Breton Augusto Brigatti Riccardo Brugnera Riccardo Bruno Antonio Budano Mario Buscemi Jose Busto Ilya Butorov Anatael Cabrera Barbara Caccianiga 蔡浩蔡啸蔡严克蔡志岩 Riccardo Callegari Antonio Cammi Agustin Campeny 曹传亚曹国富曹俊 Rossella Caruso Cédric Cerna 常劲帆 Yun Chang 陈平平 Po-An Chen 陈少敏陈旭荣 Yi-Wen Chen 陈义学陈羽陈长程捷程雅苹 Alexey Chetverikov Davide Chiesa Pietro Chimenti Artem Chukanov Gérard Claverie Catia Clementi Barbara Clerbaux Selma Conforti Di Lorenzo Daniele Corti Flavio Dal Corso Olivia Dalager Christophe De La Taille 邓智邓子艳 Wilfried Depnering Marco Diaz Xuefeng Ding 丁雅韵 Bayu Dirgantara Sergey Dmitrievsky Tadeas Dohnal Dmitry Dolzhikov Georgy Donchenko 董建蒙 Evgeny Doroshkevich Marcos Dracos Frédéric Druillole 杜然杜书先 Stefano Dusini Martin Dvorak Timo Enqvist Heike Enzmann Andrea Fabbri Ulrike Fahrendholz 范东华樊磊方建方文兴 Marco Fargetta Dmitry Fedoseev Li-Cheng Feng 冯启春 Richard Ford Amélie Fournier 甘浩男 Feng Gao Alberto Garfagnini Arsenii Gavrikov Marco Giammarchi Agnese Giaz Nunzio Giudice Maxim Gonchar 龚光华宫辉 Yuri Gornushkin Alexandre Göttel Marco Grassi Christian Grewing Vasily Gromov 顾旻皓谷肖飞古宇关梦云 Nunzio Guardone Maria Gul 郭聪郭竞渊郭万磊郭新恒郭宇航 Paul Hackspacher Caren Hagner 韩然 Yang Han Muhammad Sohaib Hassan 何苗何伟 Tobias Heinz Patrick Hellmuth 衡月昆 Rafael Herrera 贺远强侯少静 Yee Hsiung Bei-Zhen Hu 胡航胡健润胡俊胡守扬胡涛胡宇翔胡焯钧黄春豪黄桂鸿黄翰雄黄文昊黄鑫黄性涛黄永波惠加琪霍雷霍文驹 Cédric Huss Safeer Hussain Ara Ioannisian Roberto Isocrate Beatrice Jelmini Kuo-Lun Jen Ignacio Jeria 季筱璐吉星曌贾慧慧贾俊基蹇司玉蒋荻蒋炜江晓山金如意荆小平 Cécile Jollet Jari Joutsenvaara Sirichok Jungthawan Leonidas Kalousis Philipp Ka Pontificia Universidad Católica de Chile SantiagoChile IPHC Universitéde StrasbourgCNRS/IN2P3F-67037 StrasbourgFrance Pakistan Institute of Nuclear Science and Technology IslamabadPakistan INFN Catania and Dipartimento di Fisica e Astronomia dell Universitàdi Catania CataniaItaly East China University of Science and Technology ShanghaiChina University of Science and Technology of China HefeiChina Joint Institute for Nuclear Research DubnaRussia INFN Sezione di Milano and Dipartimento di Fisica dell Universitàdi Milano MilanoItaly Department of Physics Faculty of ScienceChulalongkorn UniversityBangkokThailand IJCLab UniversitéParis-SaclayCNRS/IN2P391405 OrsayFrance Department of Physics and Earth Science University of Ferrara and INFN Sezione di FerraraFerraraItaly INFN Milano Bicocca and University of Milano Bicocca MilanoItaly INFN Sezione di Padova PadovaItaly III.Physikalisches Institut B RWTH Aachen UniversityAachenGermany Eberhard Karls Universität Tübingen Physikalisches InstitutTübingenGermany Institute of High Energy Physics BeijingChina SUBATECH Universitéde NantesIMT AtlantiqueCNRS-IN2P3NantesFrance Univ.Bordeaux CNRSLP2IUMR 5797F-33170 GradignanFrance Department of Physics National Taiwan UniversityTaipei Dipartimento di Fisica e Astronomia dell’Universitàdi Padova and INFN Sezione di Padova PadovaItaly University of Roma Tre and INFN Sezione Roma Tre RomaItaly Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance Wuhan University WuhanChina INFN Milano Bicocca and Politecnico of Milano MilanoItaly National United University Miao-Li Dongguan University of Technology DongguanChina Tsinghua University BeijingChina Institute of Modern Physics Chinese Academy of SciencesLanzhouChina Institute of Physics National Yang Ming Chiao Tung UniversityHsinchu North China Electric Power University BeijingChina Sun Yat-Sen University GuangzhouChina Beijing Institute of Spacecraft Environment Engineering BeijingChina Universidade Estadual de Londrina LondrinaBrazil INFN Sez

The Jiangmen Underground Neutrino Observatory(JUNO)is a large liquid scintillator detector designed to explore many topics in fundamental *** this study,the potential of searching for proton decay in the p→νK^(+)mode with JUNO is *** kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for ***,the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed *** on these advantages,the detection efficiency for the proton decay via p→νK^(+)is 36.9%±4.9%with a background level of 0.2±0.05(syst)±0.2(stat)events after 10 years of data *** estimated sensitivity based on 200 kton-years of exposure is 9.6×1033 years,which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies.

关键词： proton decay grand unified theories JUNO liquid scintillator detector

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Feasibility and physics potential of detecting ^(8)B solar neutrinos at JUNO

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Chinese Physics C 2021年第2期45卷 93-110页

作者： Angel Abusleme Thomas Adam Shakeel Ahmad Sebastiano Aiello Muhammad Akram Nawab Ali Fengpeng An Guangpeng An Qi An Giuseppe Andronico Nikolay Anfimov Vito Antonelli Tatiana Antoshkina Burin Asavapibhop João Pedro Athayde Marcondes de André Didier Auguste Andrej Babic Wander Baldini Andrea Barresi Eric Baussan Marco Bellato Antonio Bergnoli Enrico Bernieri David Biare Thilo Birkenfeld Sylvie Blin David Blum Simon Blyth Anastasia Bolshakova Mathieu Bongrand Clément Bordereau Dominique Breton Augusto Brigatti Riccardo Brugnera Riccardo Bruno Antonio Budano Max Buesken Mario Buscemi Jose Busto Ilya Butorov Anatael Cabrera Hao Cai Xiao Cai Yanke Cai Zhiyan Cai Antonio Cammi Agustin Campeny Chuanya Cao Guofu Cao Jun Cao Rossella Caruso Cédric Cerna Jinfan Chang Yun Chang Pingping Chen Po-An Chen Shaomin Chen Shenjian Chen Xurong Chen Yi-Wen Chen Yixue Chen Yu Chen Zhang Chen Jie Cheng Yaping Cheng Alexander Chepurnov Davide Chiesa Pietro Chimenti Artem Chukanov Anna Chuvashova Gérard Claverie Catia Clementi Barbara Clerbaux Selma Conforti Di Lorenzo Daniele Corti Salvatore Costa Flavio Dal Corso Christophe De La Taille Jiawei Deng Zhi Deng Ziyan Deng Wilfried Depnering Marco Diaz Xuefeng Ding Yayun Ding Bayu Dirgantara Sergey Dmitrievsky Tadeas Dohnal Georgy Donchenko Jianmeng Dong Damien Dornic Evgeny Doroshkevich Marcos Dracos Frédéric Druillole Shuxian Du Stefano Dusini Martin Dvorak Timo Enqvist Heike Enzmann Andrea Fabbri Lukas Fajt Donghua Fan Lei Fan Can Fang Jian Fang Marco Fargetta Anna Fatkina Dmitry Fedoseev Vladko Fekete Li-Cheng Feng Qichun Feng Richard Ford Andrey Formozov Amélie Fournier Haonan Gan Feng Gao Alberto Garfagnini Alexandre Göttel Christoph Genster Marco Giammarchi Agnese Giaz Nunzio Giudice Franco Giuliani Maxim Gonchar Guanghua Gong Hui Gong Oleg Gorchakov Yuri Gornushkin Marco Grassi Christian Grewing Maxim Gromov Vasily Gromov Minghao Gu Xiaofei Gu Yu Gu Mengyun Guan Nunzio Guardone Maria Gul Cong Guo Jingyuan Guo Wanlei Guo Xinheng Guo Yuhang Guo Paul Hackspacher Caren Hagner Ran Han Yan Yerevan Physics Institute YerevanArmenia UniversitéLibre de Bruxelles BrusselsBelgium Universidade Estadual de Londrina LondrinaBrazil Pontificia Universidade Catolica do Rio de Janeiro RioBrazil Pontificia Universidad Católica de Chile SantiagoChile Universidad Tecnica Federico Santa Maria ValparaisoChile Beijing Institute of Spacecraft Environment Engineering BeijingChina Beijing Normal University BeijingChina China Institute of Atomic Energy BeijingChina Institute of High Energy Physics BeijingChina North China Electric Power University BeijingChina School of Physics Peking UniversityBeijingChina Tsinghua University BeijingChina University of Chinese Academy of Sciences BeijingChina Jilin University ChangchunChina College of Electronic Science and Engineering National University of Defense TechnologyChangshaChina Chongqing University ChongqingChina Dongguan University of Technology DongguanChina Jinan University GuangzhouChina Sun Yat-Sen University GuangzhouChina Harbin Institute of Technology HarbinChina University of Science and Technology of China HefeiChina The Radiochemistry and Nuclear Chemistry Group in University of South China HengyangChina Wuyi University JiangmenChina Shandong University JinanChina Institute of Modern Physics Chinese Academy of SciencesLanzhouChina Nanjing University NanjingChina Guangxi University NanningChina East China University of Science and Technology ShanghaiChina School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghaiChina Tsung-Dao Lee Institute Shanghai Jiao Tong UniversityShanghaiChina Institute of Hydrogeology and Environmental Geology Chinese Academy of Geological SciencesShijiazhuangChina Nankai University TianjinChina Wuhan University WuhanChina Xi’an Jiaotong University Xi’anChina Xiamen University XiamenChina School of Physics and Microelectronics Zhengzhou UniversityZhengzhouChina Institute of Physics National Chiao-Tung University Hsinchu National United University Miao-Li Department of Physics National T

The Jiangmen Underground Neutrino Observatory(JUNO)features a 20 kt multi-purpose underground liquid scintillator sphere as its main *** of JUNO's features make it an excellent location for^8B solar neutrino measurements,such as its low-energy threshold,high energy resolution compared with water Cherenkov detectors,and much larger target mass compared with previous liquid scintillator *** this paper,we present a comprehensive assessment of JUNO's potential for detecting^8B solar neutrinos via the neutrino-electron elastic scattering process.A reduced 2 MeV threshold for the recoil electron energy is found to be achievable,assuming that the intrinsic radioactive background^(238)U and^(232)Th in the liquid scintillator can be controlled to 10^(-17)g/*** ten years of data acquisition,approximately 60,000 signal and 30,000 background events are *** large sample will enable an examination of the distortion of the recoil electron spectrum that is dominated by the neutrino flavor transformation in the dense solar matter,which will shed new light on the inconsistency between the measured electron spectra and the predictions of the standard three-flavor neutrino oscillation *** m^(2)_(21)=4.8times10^(-5);(7.5times10^(-5))eV^(2),JUNO can provide evidence of neutrino oscillation in the Earth at approximately the 3sigma(2sigma)level by measuring the non-zero signal rate variation with respect to the solar zenith ***,JUNO can simultaneously measureDelta m^2_(21)using^8B solar neutrinos to a precision of 20% or better,depending on the central value,and to sub-percent precision using reactor antineutrinos.A comparison of these two measurements from the same detector will help understand the current mild inconsistency between the value of Delta m^2_(21)reported by solar neutrino experiments and the KamLAND experiment.

关键词： neutrino oscillation solar neutrino JUNO

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Dynamic behavior of polar nanoregions in re-entrant relaxor 0.6Bi(Mg1/2Ti1/2)O3-0.4PbTiO3

arXiv

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arXiv 2020年

作者： Chen, Kaiyuan Zhang, Qi Liu, Jia Wang, Jie Lan, Zhencheng Fang, Liang Hu, Changzheng Luo, Nengneng Peng, Biaolin Long, Changbai Wang, Dawei Liu, Laijun Guangxi Key Laboratory of Optical and Electronic Materials and Devices College of Materials Science and Engineering Guilin University of Technology Guilin541004 China BCMaterials Basque center for materials application & nanostructures Basque Spain School of Microelectronics State Key Laboratory for Mechanical Behaviour of Materials Xi’an Jiaotong University Xi’an710049 China Key Laboratory for RF Circuits and Systems Ministry of Education Key Laboratory of Large Scale Integrated Design Hangzhou Dianzi University Hangzhou310018 China School of Physical Science & Technology Guangxi Key Laboratory for Relativistic Astrophysics Guangxi University Nanning530004 China School of Advanced Materials and Nanotechnology Xidian University Xi’an710071 China

The existence of polar nanoregions is the most important characteristic of ferroelectric relaxors, however, the size determination and dynamic of PNRs remains uncertain. We reveal a re-entrant relaxor behavior and ferroelectric-paraelectric transition coexists in complex perovskite oxide 0.6Bi(Mg1/2Ti1/2)O3-0.4PbTiO3. Two dielectric anomalies (i) the low-temperature re-entrant relaxor transition and (ii) the high-temperature diffuse phase transition (DPT) were described by the phenomenological statistical model. The sizes of the two kinds of polar nanoregions (PNRs) corresponding to two ferroelectric states were obtained. The dynamic of PNRs were analyzed using isothermal electrical modulus, which shows three critical temperatures associated with the diffuse phase transition, the formation and freezing of PNRs, respectively. The temperature evolution of the PNRs evolution depends on the stoichiometry of bismuth. The results provide new insights into the dynamic behavior of PNRs and the modification way of re-entrant relaxor behavior. Copyright © 2020, The Authors. All rights reserved.

关键词： Dielectric relaxation

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A load balanced mapping for spiking neural network 2

A load balanced mapping for spiking neural network

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2nd International Conference on Image, Vision and Computing, ICIVC 2017

作者： Yande, Xiang Jianyi, Meng Ma, De College of Information Science and Electronic Engineering Zhejiang University Hangzhou China State Key Laboratory of ASIC and System Department of Microelectronics Fudan University Shanghai China MOE Key Laboratory of RF Circuits and Systems Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781509062379

Network-on-Chip (NoC) provides a scalable and packet-based inter-connected architecture for spiking neural networks (SNNs). However, existing neural mapping strategies just distribute all neurons in a population to an on-chip network core or nearby cores sequentially. The neurons within a population take a huge time cost for handling spikes, which results to uneven workload distribution among different on chip network nodes. This paper presents a NoC-based SNN mapping that makes workload balance among different nodes, aiming to accelerate application execution time. The experimental results show that proposed mapping strategy reduces application execution time by average 24%. © 2017 IEEE.

关键词： Network-on-chip

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Design of high-efficiency digital-control multi-topology step-down switched capacitor converter 35

Design of high-efficiency digital-control multi-topology ste...

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2015 35th IEEE International Conference on Electronics and Nanotechnology, ELNANO 2015

作者： Melikyan Vazgen, Sh. Galstyan Vache, A. Department of Microelectronics Circuits and Systems State Engineering University of Armenia Synopsys Armenia CJSC Yerevan Armenia

ISBN: (纸本)9781467365345

This paper presents a multi-topology step-down switched-capacitor (SC) converter with a novel digital control. The feedback control system performs digital control over operating frequency and topology of the converter to efficiently modify the SC configuration depending on actual current load as well as required output voltage. The feedback is designed without the usage of reference voltages which provides easy integration of proposed SC converter in digital systems. The converter achieves maximal efficiency of 88%, while providing a wide range of load current and low level of output voltage ripple. Due to the multi-topology structure, high efficiency is provided over 1.3V of input voltage. The converter is designed in 28nm CMOS process using the proposed technique. © 2015 IEEE.

关键词： Frequency modulation

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Multi-rate Clock-Data recovery solution in high speed serial links

Multi-rate Clock-Data recovery solution in high speed serial...

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IEEE International Conference on Electronics and Nanotechnology (ELNANO)

作者： Melikyan Vazgen Sahakyan Arthur Shishmanyan Aram Hekimyan Arsen Department of Microelectronics Circuits and Systems State Engineering University of Armenia Yerevan Armenia

Clock-Data recovery (CDR) architecture with multirate option in receiver of a high-speed serial link presented. Proper clock phase choosing and let it track data phase shifts over time are the main difficulties of all kind of CDR structures. This system helps to shift reference clock according to data signal phase to sample it in the most secure way regarding data errors and information loses. Meanwhile, since data signal can change phase over time due to noises and other uncertainties (jitter in the input point of receiver), CDR system should have some tracking option which could track data phase shifts over time and accordingly change phase of reference clock which coming from PLL.

关键词： Clocks Jitter Receivers Mixers Bit error rate Universal Serial Bus Simulation

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Design of high-efficiency digital-control multi-topology step-down switched capacitor converter

Design of high-efficiency digital-control multi-topology ste...

引用

IEEE International Conference on Electronics and Nanotechnology (ELNANO)

作者： Sh. Melikyan Vazgen A. Galstyan Vache Department of Microelectronics Circuits and Systems State Engineering University of Armenia Yerevan Armenia

关键词： Clocks Topology Switches Frequency conversion Switching circuits Voltage control

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