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On non-von Neumann flexible neuromorphic vision sensors

npj Flexible Electronics 2024年第1期8卷 638-663页

作者： Hao Wang Bin Sun Shuzhi Sam Ge Jie Su Ming Liang Jin Institute for Future Shandong Key Laboratory of Industrial Control TechnologySchool of AutomationQingdao UniversityQingdao 266071China College of Electronic and Information Engineering Qingdao UniversityQingdao 266071China Department of Electrical and Computer Engineering and Institute for Functional Intelligent MaterialsNational University of SingaporeSingapore 117583Singapore

The structure andmechanismof thehuman visual system contain rich treasures,and surprising effects can be achieved by simulating the human visual *** this article,starting from the human visual system,we compare and discuss the discrepancies between the human visual system and traditional machine vision *** the wide variety and large volume of visual information,the use of nonvon Neumann structured,flexible neuromorphic vision sensors can effectively compensate for the limitations of traditional machine vision systems based on the von Neumann ***,this article addresses the emulation of retinal functionality and provides an overview of the principles and circuit implementation methods of non-von Neumann computing ***,in terms of mimicking the retinal surface structure,this article introduces the fabrication approach for flexible sensor ***,this article analyzes the challenges currently faced by non-von Neumann flexible neuromorphic vision sensors and offers a perspective on their future development.

关键词： Neumann system starting

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Alternative non-Gaussianity measures for quantum states based on quantum fidelity

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Chinese Physics B 2022年第3期31卷 192-200页

作者： Cheng Xiang Shan-Shan Li Sha-Sha Wen Shao-Hua Xiang College of Electrical and Information Engineering Huaihua UniversityHuaihua 418008 China Hunan Provincial Key Laboratory of Ecological Agriculture Intelligent Control Technology Huaihua 418008China

We propose three alternative measures for non-Gaussianity of quantum states: sine distance, Bures angle, and Bures distance, which are based on quantum fidelity introduced by Wang [Phys. Lett. A 373 58(2008)]. Using them, we evaluate the non-Gaussianity of some relevant single-mode and two-mode non-Gaussian states and find a good consistency of the three examined measures. In addition, we show that such metrics can exactly quantify the degree of Gaussianity of even Schrödinger-cat-like states of small amplitudes that can not be measured by other known non-Gaussianity measures such as the Hilbert–Schmidt metric and the relative entropy metric. We make a comparative study between all existing nonGaussianity measures according to the metric axioms and point out that the sine distance is the best candidate among them.

关键词： non-Gaussianity quantum fidelity non-Gaussian states sine metric

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Side-chain cyclization enhancing molecular rigidity and π-π stacking yields as-cast binary organic solar cells with 19.1% efficiency

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Science China Chemistry 2025年第06期68卷 2500-2512页

作者： Lang Li Wei Gao Ruijie Ma Xinjing Zhao Top Archie Dela Pe?a Jiaying Wu Jian-Xin Tang Zhanhua Wei Xiamen Key Laboratory of Optoelectronic Materials and Advanced Manufacturing Institute of Luminescent Materials and Information Displays College of Materials Science and Engineering Huaqiao University Department of Electrical and Electronic Engineering Research Institute for Smart Energy (RISE) Photonic Research Institute (PRI) The Hong Kong Polytechnic University Advanced Materials Thrust Function Hub The Hong Kong University of Science and Technology Nansha Macao Institute of Materials Science and Engineering (MIMSE) Faculty of Innovation Engineering Macau University of Science and Technology

High-performance as-cast organic solar cells(OSCs) are rarely reported due to the challenges in achieving high-quality active layer morphology via a single-step process. Herein, four small molecule acceptors(SMAs) substituted with cyclic alkyl chains of varying carbon numbers were synthesized and utilized to fabricate highly efficient as-cast OSCs. The side-chain cyclization strategy significantly enhances molecular rigidity and strengthens intermolecular packing, particularly in Se-Cb, which exhibits an excellent three-dimensional(3D) stacking framework with a π-π stacking distance as short as 3.34 ?. As the size of cyclic alkyl chain increases, the packing mode of SMA single crystals shift from 3D to 2D, accompanied by a greater π-π stacking distance due to increased steric hindrance. As-cast binary devices based on D18/Se-Cb achieved a record power conversion efficiency(PCE) of 19.1% with a fill factor(FF) exceeding 80%, and a certified value of 18.45%. Se-Cb forms a more uniform vertical phase separation morphology than the control SMA within the D18 matrix, enhancing carrier transport and significantly suppressing sub-nanosecond bimolecular recombination. This study systematically investigates the effects of cyclic alkyl chain substitution on the properties and photovoltaic performance of SMAs, identifying cyclobutyl as a promising candidate for efficient as-cast OSCs with high FF.

关键词： organic solar cells small molecule acceptor cyclic alkyl chain as-cast selenophene

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Topology and admittance estimation:Precision limits and algorithms

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iEnergy 2023年第4期2卷 297-307页

作者： Ning Zhang Yuxiao Liu Fangyuan Si Qingchun Hou Audun Botterud Chongqing Kang Department of Electrical Engineering Tsinghua UniversityBeijing 100084China School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China Laboratory of Information and Decision Systems Massachusetts Institute of TechnologyCambridgeMA 02139 USA

Distribution grid topology and admittance information are essential for system planning,operation,and *** many distribution grids,missing or inaccurate topology and admittance data call for efficient estimation ***,measurement data may be insufficient or contaminated with large noise,which will fundamentally limit the estimation *** work explores the theoretical precision limits of the topology and admittance estimation(TAE)problem with different measurement devices,noise levels,and numbers of *** this basis,we propose a conservative progressive self-adaptive(CPS)algorithm to estimate the topology and *** results on IEEE 33 and 141-bus systems validate that the proposed CPS method can approach the theoretical precision limits under various measurement settings.

关键词： Distribution grids topology estimation admittance estimation data-driven Newton−Raphson method

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InGaPχ^((2))integrated photonics platform for broadband,ultra-efficient nonlinear conversion and entangled photon generation

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Light(Science & Applications) 2024年第12期13卷 3090-3098页

作者： Joshua Akin Yunlei Zhao Yuvraj Misra A.K.M.Naziul Haque Kejie Fang Holonyak Micro and Nanotechnology Laboratory and Department of Electrical and Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Illinois Quantum Information Science and Technology Center University of Illinois at Urbana-ChampaignUrbanaIL 61801USA

Nonlinear optics plays an important role in many areas of science and *** advance of nonlinear optics is empowered by the discovery and utilization of materials with growing optical *** we demonstrate an indium gallium phosphide(InGaP)integrated photonics platform for broadband,ultra-efficient second-order nonlinear *** InGaP nanophotonic waveguide enables second-harmonic generation with a normalized efficiency of 128,000%/W/cm^(2)at 1.55μm pump wavelength,nearly two orders of magnitude higher than the state of the art in the telecommunication C ***,we realize an ultra-bright,broadband time-energy entangled photon source with a pair generation rate of 97 GHz/mW and a bandwidth of 115 nm centered at the telecommunication C *** InGaP entangled photon source shows high coincidence-to-accidental counts ratio CAR>10^(4)and two-photon interference visibility>98%.The InGaP second-order nonlinear photonics platform will have wide-ranging implications for non-classical light generation,optical signal processing,and quantum networking.

关键词： nonlinear optics coincidence

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A Novel Grades Prediction Method for Undergraduate Students by Learning Explicit Conditional Distribution

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4837-4848页

作者： Zhang, Na Liu, Ming Wang, Lin Liu, Shuangrong Sun, Runyuan Yang, Bo Zhu, Shenghui Li, Chengdong Yang, Cheng Cheng, Yuhu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Shandong Key Laboratory of Intelligent Buildings Technology Jinan250101 China University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China Quan Cheng Laboratory Jinan250100 China Shandong Jianzhu University Shandong Key Laboratory of Intelligent Buildings Technology Jinan250101 China Shandong Jianzhu University School of Information and Electrical Engineering Jinan250101 China Ministry of Education Engineering Research Center of Intelligent Control for Underground Space Xuzhou221116 China

Educational data mining (EDM) offers an effective solution to predict students' course grades in the next term. Conventional grade prediction methods can be viewed as regressing an expectation of the probability distribution of the student's grade, typically called single-value grade prediction. The reliable prediction outcomes of these methods depend on the complete input information related to students. However, next-term grade prediction often encounters the challenge of incomplete input information due to the inaccessibility of future data and the privacy of data. In this scenario, single-value grade prediction struggles to assess students' academic status, as it may not be represented and assessed by relying on a singular expectation value. This limitation increases the risk of misjudgment, and may lead to errors in educational decision-making. Considering the challenge of collecting complete input information, we shift from traditional single-value predictions to forecasting the explicit probability distribution of the course grade. The probability distribution of the grade can assess the students' academic status by providing probabilities corresponding to all possible grade values rather than relying solely on an expectation value, which offers the foundation to support the educators' decision-making. In this article, the course grade distribution prediction (CGDP) model is proposed, aiming to estimate an explicit conditional probability distribution of course grades in the next term. This model can identify at-risk students, offering comprehensive decision-making information for educators and students. To ensure precise distribution predictions, a calibration method is also employed to improve the alignment between predicted and actual probabilities. Experimental results verify the effectiveness of the proposed model in early grade warning for undergraduates, based on real university data. © 2020 IEEE.

关键词： Probability distributions

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Deep Reinforcement Learning Based Approach for Dynamic Optimal Power Flow in Active Distribution Network 41

Deep Reinforcement Learning Based Approach for Dynamic Optim...

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第41届中国控制会议

作者： Xinghua Liu Bangji Fan Jiaqiang Tian Department of Power Grid Information and Control Engineering School of Electrical EngineeringXi'an University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The dynamics and randomness of the active distribution network(ADN) bring many difficulties to optimal power flow(OPF).In this paper,we propose a deep reinforcement learning method to solve the dynamic optimal power flow(DOPF)of ADN including photovoltaic(PV) power and energy storage systems(ESS).In the distributed generations(DG) modeling of ADN,PV and ESS are treated as PQ nodes,constant power factor control is adopted in the reactive power management of PV to enhance the universality of the *** from the traditional methods,the OPF covering multiple periods is described as a Markov process,which takes the reactive output of PV and the active and reactive output of ESS as the *** the continuity of actions,the deep deterministic policy gradient(DDPG) algorithm is introduced to train the agent to obtain the actions at each time of the ***,the method in this paper is verified in an improved IEEE 33-bus distribution network with real data of PV power and *** experimental results show that the proposed method can adjust the decision-making of the agent according to the real-time active output of DG and loads,to minimize the total active power network loss in a day.

关键词： Dynamic optimal power flow active distribution network distributed generations deep reinforcement learning

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Data-driven finite-time adaptive attitude tracking control for spacecraft

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Advances in Space Research 2025年第12期75卷 8780-8791页

作者： Wang, Jianhui He, Guangping Bian, Guibin Geng, Shixiong College of Mechanical & Energy Engineering Beijing University Of Technology Beijing100124 China Department of Mechanical and Electrical Engineering North China University of Technology Beijing100144 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

This paper proposes a novel data-driven finite-time adaptive control method for the spacecraft attitude tracking control problem with inertial uncertainty. Based on the dynamic regression extension technique, the disturbance unit matrix is introduced, and the parameter estimation law in the form of algebraic equations is presented, which realizes the arbitrarily small convergence of parameter estimation error. The convergence of parameter estimation errors is verified through stability analysis. Globally non-singular fast terminal sliding mode control is designed to achieve finite-time arrival of the sliding surface and convergence of the system state error. The stability analysis of the closed-loop system demonstrates the effectiveness of the proposed method. Furthermore, the effectiveness and superiority of the proposed method are verified through numerical simulations of spacecraft attitude tracking control. © 2025 COSPAR

关键词： Attitude control

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Digital Twin-Based Automated Fault Diagnosis in Industrial IoT Applications

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Computers, Materials & Continua 2023年第4期75卷 183-196页

作者： Samah Alshathri Ezz El-Din Hemdan Walid El-Shafai Amged Sayed Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Security Engineering LabPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Energy Engineering College of Engineering&TechnologyArab Academy for Science Technology&Maritime TransportSmart Village CampusEgypt

In recent years, Digital Twin (DT) has gained significant interestfrom academia and industry due to the advanced in information technology,communication systems, Artificial Intelligence (AI), Cloud Computing (CC),and Industrial Internet of Things (IIoT). The main concept of the DT isto provide a comprehensive tangible, and operational explanation of anyelement, asset, or system. However, it is an extremely dynamic taxonomydeveloping in complexity during the life cycle that produces a massive amountof engendered data and information. Likewise, with the development of AI,digital twins can be redefined and could be a crucial approach to aid theInternet of Things (IoT)-based DT applications for transferring the data andvalue onto the Internet with better decision-making. Therefore, this paperintroduces an efficient DT-based fault diagnosis model based on machinelearning (ML) tools. In this framework, the DT model of the machine isconstructed by creating the simulation model. In the proposed framework,the Genetic algorithm (GA) is used for the optimization task to improvethe classification accuracy. Furthermore, we evaluate the proposed faultdiagnosis framework using performance metrics such as precision, accuracy,F-measure, and recall. The proposed framework is comprehensively examinedusing the triplex pump fault diagnosis. The experimental results demonstratedthat the hybrid GA-ML method gives outstanding results compared to MLmethods like LogisticRegression (LR), Na飗e Bayes (NB), and SupportVectorMachine (SVM). The suggested framework achieves the highest accuracyof 95% for the employed hybrid GA-SVM. The proposed framework willeffectively help industrial operators make an appropriate decision concerningthe fault analysis for IIoT applications in the context of Industry 4.0.

关键词： Automated fault diagnosis control system ML AI CC IIoT digital twins genetic algorithm GA-ML technique

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Hybrid Digital-Analog Semantic Communications

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IEEE Journal on Selected Areas in Communications 2025年第7期43卷 2478-2492页

作者： Xie, Huiqiang Qin, Zhijin Han, Zhu Letaief, Khaled B. Jinan University College of Information Science and Technology Guangzhou China Tsinghua University Department of Electronic Engineering Beijing100084 China State Key Laboratory of Space Network and Communications Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China University of Houston Department of Electrical and Computer Engineering Houston United States The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong

Digital and analog semantic communications (SemCom) face inherent limitations such as data security concerns in analog SemCom, as well as leveling-off and cliff-edge effects in digital SemCom. In order to overcome these challenges, we propose a novel SemCom framework and a corresponding system called HDA-DeepSC, which leverages a hybrid digitalanalog approach for multimedia transmission. This is achieved through the introduction of analog-digital allocation and fusion modules. To strike a balance between data rate and distortion, we design new loss functions that take into account long-distance dependencies in the semantic distortion constraint, essential information recovery in the channel distortion constraint, and optimal bit stream generation in the rate constraint. Additionally, we propose denoising diffusion-based signal detection techniques, which involve carefully designed variance schedules and sampling algorithms to refine transmitted signals. Through extensive numerical experiments, we will demonstrate that HDA-DeepSC exhibits robustness to channel variations and is capable of supporting various communication scenarios. Our proposed framework outperforms existing benchmarks in terms of peak signal-to-noise ratio and multi-scale structural similarity, showcasing its superiority in semantic communication quality. © 1983-2012 IEEE.

关键词： Digital communication systems

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