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IEEE International Conference on Microelectronic Test Structures

作者： Hao-Chiao Hong Long-Yi Lin Bo-Chang Chen Institute of Electrical and Computer Engineering Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Novatek MicroElectronics Corp. Hsinchu Taiwan

Computing-in-memory (CIM) is a promising technique for energy-efficiently conducting the massive amount of required multiply-and-accumulate (MAC) calculations in neural networks (NNs). The read-decoupled 8T (RD8T) SRAM cell is popular in the CIM designs because of being read disturbance free. However, local process variations may lead significant errors to the CIM results. This work proposes an accurate on-chip test circuit design for characterizing the output current of every RD8T SRAM cell in a 8-kb RD8T SRAM array fabricated in 90nm CMOS. The experimental results show the detailed and accurate spatial distribution of the RD8T cells which helps optimize the CIM circuit design.

关键词： Fabrication Graphical models Nonvolatile memory SRAM cells Phase change random access memory Energy efficiency Circuit synthesis

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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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Resilient distributed optimization under mobile malicious attacks

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IFAC-PapersOnLine 2023年第2期56卷 997-1002页

作者： Yuan Wang Changxin Liu Hideaki Ishii Karl Henrik Johansson Department of Robotics Hunan University Changsha China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden Department of Computer Science Tokyo Institute of Technology Yokohama Japan

This article addresses the distributed optimization problem in the presence of malicious adversaries that can move within the network and induce faulty behaviors in the attacked nodes. We first investigate the vulnerabilities of a consensus-based secure distributed optimization protocol under mobile adversaries. Then, a modified resilient distributed optimization algorithm is proposed. We develop conditions on the network structure for both complete and non-complete directed graph cases, under which the proposed algorithm guarantees that the estimates by regular nodes converge to the convex combination of the minimizers of their local functions. Simulations are carried out to verify the effectiveness of our approach.

关键词： Fault-tolerant distributed optimization multi-agent systems network security mobile adversary agents

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Broadband usage for rural communities in the North Island of Aotearoa New Zealand

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Intelligent and Converged Networks 2022年第3期3卷 244-259页

作者： Ming Xiang William Liu Edmund Lai Jairo Gutierrez Luca Chiaraviglio Jinsong Wu Control Science and Engineering South China University of TechnologyGuangzhou 510300Chinaand also with the South China Sea Institute of Planning and Environmental ResearchMinistry of Natural ResourcesGuangzhou 510300China Department of Computer Science and Software Engineering School of EngineeringComputer and Mathematical SciencesAuckland University of TechnologyAuckland 1010New Zealand Department of Electronic Engineering University of Rome“Tor Vergata”Rome 00133Italy Consorzio Nazionale Interuniversitario per le Telecomunicazioni(CNIT) Parma 43124Italy Department of Electrical Engineering Universidad de ChileSantiago 92101Chile

New Zealand government’s Rural Broadband Initiative(RBI)aims to invest 400 million New Zealand dollar to provide 99%of New Zealanders with access to 50 Mbps peak broadband speed,with the remaining 1%at 10 Mbps by *** 2017,stage 1 of the RBI has been completed,and research is needed to find out the level of usage,proficiency,and productivity achieved by ***,a survey was carried out to learn whether the rural residents and their communities are making good use of the new fast broadband *** survey collected data from 217 rural residents from North Island,and the results indicate that about half of the interview respondents are satisfied with the new broadband speed and the reliability which is offered by RBI stage ***,there is about 28%of the respondents disagreed with *** majority of the Internet uses for rural residents are information searching,reading news,online entertainment,and online *** that,only a small proportion of respondents know how to utilize the Internet in their work/business and benefit/profit from it,e.g.,using cloud technology capabilities and online marketing campaigns,*** ***,we argue that information and communications technologies(ICT)adoption is not only the availability of the infrastructure but also the beneficial outcomes of Internet *** other words,Internet skills in-depth training and education need to catch up with the infrastructure deployment,which is useful to fuel the digital productivity and inclusion for booming rural *** survey data-driven findings presented in this paper could serve as a reference to inform government policymakers and those who wish to create,invest,and take actions to speed up the economic and social growth of rural communities in Aotearoa New Zealand through the Internet while shifting from the Internet speed and traffic volume-driven to a more effective Internet connectivity and value-added driven rural economy.

关键词： data driven approach data-supported decision and policy making digital exclusion information and communications technologies(ICT)adoption effective connectivity rural broadband usage rural economic development

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Optimizing Electrocardiogram Signal Augmentation for Realistic Synthetic Data in Deep Learning Model

Optimizing Electrocardiogram Signal Augmentation for Realist...

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Muhammad Farhan Safdar Piotr Pałka Ahmed Al Faresi Robert Marek Nowak Institute of Computer Science Warsaw University of Technology Poland Institute of Control and Computation Engineering Warsaw University of Technology Poland College of Information Technology United Arab Emirates University UAE

ISBN: (数字)9788362065486

ISBN: (纸本)9798350373806

Electrocardiograms (ECG) are non-invasive signals and have proven useful in assessing the heart condition. Given the necessity for extensive datasets in ECG classification using deep learning (DL) models, there is a critical imperative to devise data augmentation methods capable of generating synthetic but realistic dataset suitable for training DL model. In this study, we propose a novel approach for augmenting ECG signals, aiming to produce realistic signals while optimizing memory usage and resource requirements. Building upon our previous work in ECG signal augmentation, we revisit the methodology to address limitations observed in the generation of synthetic signals. The existing method segmented ECG signals into fixed-length segments and combined them, occasionally resulting in unrealistic heart cycles within the signals in extreme condition. To address this issue, our proposed technique incorporates R peak detection, signal segmentation, and reordering based on the R-peaks information. We evaluated the proposed method using three benchmark datasets, including PTB-XL, Chapman-Shaoxin from PhysioNet, and the dataset from China Physiological Signal Challenge 2018 (CPSC-2018), for classifying atrial fibrillation from normal samples. Our approach achieved an accuracy of 0.83, sensitivity of 0.86, specificity of $0.80, F_{1}$-score of 0.83, and precision of 0.80. These results underscore the effectiveness and efficiency of our method in augmenting ECG signals for various applications in healthcare and biomedical research.

关键词： Training Heart Deep learning Biological system modeling Signal processing algorithms Electrocardiography Data augmentation Data models Classification algorithms Synthetic data

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Recognition of Power Quality Disturbance Based on RCNN 4

Recognition of Power Quality Disturbance Based on RCNN

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2022 4th International Conference on Artificial Intelligence and computer Science, AICS 2022

作者： Fan, Rui Li, Huipeng Xiao, Heju Wang, Hong Qi, Linhai State Grid Shanxi Electric Power Company Electric Power Research Institute Shanxi Taiyuan China School of Control and Computer Engineering North China Electric Power University Beijing China

With the development of the smart grid, the problem of power quality disturbance is becoming more and more serious. To improve the classification ability of power quality disturbance signals, this paper designs a recurrent convolutional neural network model to realize the classification and identification of power quality disturbance signals. The model first uses the bidirectional long short-term memory neural network module to encode the disturbance signal. Then it uses the convolutional layer to perform spatial feature extraction and enforces the disturbance classification through the fully connected layer. The model is verified and analyzed by simulation data, which shows that the model has both good generalization ability and higher accuracy. © 2022 institute of Physics Publishing. All rights reserved.

关键词： Neural network models

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Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 47-63页

作者： Yongliang Yang Zihao Ding Rui Wang Hamidreza Modares Donald C.Wunsch Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education School of Automation&Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China School of Automation Beijng Institute TechnologyBeijing 100081China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Mechanical Engineering Department Michigan State UniversityEast LansingMI 48824 USA Department of Electrical&Computer Engineering Missouri University of Science&TechnologyRollaMO 65401 USA

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the *** presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller *** task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the ***-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance *** the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity *** this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task *** simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.

关键词： Adaptive impedance control data-driven method human-robot interaction(HRI) reinforcement learning velocity-free

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On Finite Word Length Computing Error of Fixed-Point SAR Imaging Processing*

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Chinese Journal of Electronics 2025年第3期23卷 645-648页

作者： Yizhuang Xie Bocheng Zhu Wen Yan Weijie Zhang School of Information and Electronics Beijing Institute of Technology Beijing China School of Electronics Engineering and Computer Science Peking University Beijing China Science and Technology on Electronic Information Control Laboratory Chengdu China

Synthetic aperture radar (SAR) imaging system is generally realized by fixed-point with the purpose of reducing system implementation scale and enhancing real-time performance. Finite word length computing error of fixed-point SAR imaging system is studied. The characteristic of computing error in SAR imaging system is analyzed. A finite word length computing error model of SAR imaging system is built, by means of which the empirical formula of system's output noise-to-signal ratio is derived. Based on the empirical formula, SAR imaging system processing word length is presented according to different processing granularities. The validity of this proposed finite word length computing error model of SAR imaging system is verified by system level fixed-point simulation.

关键词： Computational modeling Imaging Transforms Radar polarimetry Real-time systems Synthetic aperture radar System implementation

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Rollover Prevention control for Autonomous Vehicles with High Centers of Gravity Considering Input Saturation

Rollover Prevention Control for Autonomous Vehicles with Hig...

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第43届中国控制会议

作者： Linying Lu Ting Zhang Lin Qi Jiayi Fang Xiaohong Jiao School of Electrical Engineering Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University School of Vehicle and Mobility Tsinghua University School of Mechanical Engineering Beijing Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

A fixed-time terminal sliding mode control(FTSMC) strategy based on extended state observer for cooperative control of rollover prevention and trajectory tracking is proposed to enable the high-center-of-gravity autonomous vehicles to ensure tracking performance and prevent rollover. The FTSMC allows the errors to converge globally to a predefined arbitrarily small set centered at zero in a fixed time and then exponentially converge to zero while weakening the influence of input saturation on the controller by compensating the auxiliary system of input saturation. Simulation comparisons with existing results verify the effectiveness and advantages of the designed strategy under the MATLAB/Simulink environment.

关键词： Autonomous Vehicles Fixed-time Rollover Prevention Input Saturation

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Industrial Scenario of Renewable Energy-Based Electromobility 3rd

Industrial Scenario of Renewable Energy-Based Electromobilit...

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3rd International Conference on Energy Systems, Drives and Automations, ESDA 2020

作者： Szymanski, Jerzy Zurek-Mortka, Marta Faculty of Transport Electrical Engineering and Computer Science Kazimierz Pulaski University of Technology and Humanities Radom Poland Department of Control Systems Lukasiewicz Research Network Institute for Sustainable Technology Radom Poland

ISBN: (纸本)9789811672736

The article presents the concept of a hybrid network topology in the enterprises with the use of a solar power plant and energy storage as well as a drive frequency converter for charging of transportation battery of wheels vehicles and powering of electric caterpillar mining machines. Two important functionalities of the drive frequency converter as a unidirectional EV battery charger and for powering electric motors are presented. The obtained results of the simulation and experimental tests of the presented model confirm the possibility of controlling the DC current value of connected to drive frequency converter of the diode rectifier unit charging the EV battery. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Solar energy

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