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4th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2021

作者： Zha, Wende Feng, Botao Chung, Kwok L. Deng, Li College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China School of Computer Science and Engineering Huizhou University Huizhou516007 China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9781665432030

In this paper, a tri-band unidirectional printed antenna is presented. By employing a torch-shaped structure to cooperate with a pair of side-by-side rectangular patches, triple band characteristics are realized. Simulation results show that the working frequency bands are 806-960 MHz, 1.71-2.7 GHz and 3.3-3.7 GHz, respectively, which cover the LTE700/ GSM850/ GSM900, S-band and WLAN frequency bands. A compact and simple structure with good radiation characteristics is achieved by the proposed antenna, which is suitable for multi-frequency wireless communications. ©2021 IEEE

关键词： Microstrip antennas

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Multi-stage Objective Function Optimized Hand-Eye Self-calibration of Robot in Autonomous Environment 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Liu, Kaibo Zheng, Wangli Min, Huasong Lin, Yunhan School of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Hubei Wuhan430065 China State Grid Electric Power Research Institute Jiangsu Nanjing211106 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Hubei Wuhan430081 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

In the application scenario of robot autonomous tasks, the robot needs to be able to complete calibration online and automatically to achieve self-maintenance, which differs from traditional robot hand-eye calibration in that the traditional robot hand-eye calibration requires a dedicated calibration board to assist offline completion. Aiming at the problem that the existing self-calibration methods cannot be optimized as a whole, which leads to low accuracy and instability of the solution, a multi-stage objective function optimization self-calibration algorithm is proposed, which describes the solution of hand-eye self-calibration as a minimization objective function problem involving multiple stages. An optimization method based on the minimization of re-projection error is designed to compensate for the results, which uses an efficient Oriented fast and rotated brief (ORB) feature extraction algorithm and introduces a scoring mechanism to retain more correct matching points in the feature matching stage. Two different types of experiments were designed to validate our method. One is a single camera dataset experiment, which shows that our method is more accurate and robust than the existing self-calibration method;the other is an application platform experiment, which verifies the feasibility and availability of our method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Calibration

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Detection of trace metals in water by filamentand plasma-grating-induced breakdown spectroscopy

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Advanced Photonics Nexus 2023年第1期2卷 70-79页

作者： Mengyun Hu Fangfang Li Shencheng Shi Yu Qiao Jinman Ge Xiaojun Li Heping Zeng East China Normal University State Key Laboratory of Precision SpectroscopyShanghaiChina Chongqing Institute of East China Normal University Chongqing Key Laboratory of Precision OpticsChongqingChina University of Shanghai for Science and Technology School of Optical-Electrical and Computer EngineeringEngineering Research Center of Optical Instrument and System(Ministry of Education)Shanghai Key Laboratory of Modern Optical SystemShanghaiChina China Academy of Space Technology(Xi’an) National Key Laboratory of Science and Technology on Space MicrowaveXi’anShaanxiChina Shanghai Research Center for Quantum Sciences ShanghaiChina Chongqing Institute for Brain and Intelligence Guangyang Bay LaboratoryChongqingChina

Filament-and plasma-grating-induced breakdown spectroscopy(F-GIBS)was demonstrated as an efficient technique for sensitive detection of metals in water,where plasma gratings were established through synchronized nonlinear interaction of two noncollinear filaments and an additional filament was generated with another fs laser beam propagating along their bisector.A water jet was constructed vertically to the three coplanar filaments,overcoming side effects from violent plasma explosion and bubble *** distinct regimes of different mechanisms were validated for nonlinear couplings of the third filament with plasma *** the third filament was temporally overlapped with the two noncollinear filaments in the interaction zone,all the three filaments participated in synchronous nonlinear interaction and plasma grating structures were altered by the addition of the third *** the third filament was positively or negatively delayed,the as-formed plasma gratings were elongated by the delayed third filament,or plasma gratings were formed in the presence of plasma expansion of the ahead third filament,*** F-GIBS for trace metal detection in water,significant spectral line enhancements were observed.

关键词： laser-induced breakdown spectroscopy filament and plasma-gratings induced breakdown spectroscopy filaments plasma gratings grating induced breakdown spectroscopy

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Towards silicon photonic neural networks for artificial intelligence

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Science China(Information Sciences) 2020年第6期63卷 105-118页

作者： Bowen BAI Haowen SHU Xingjun WANG Weiwen ZOU State Key Laboratory of Advanced Optical Communications System and Networks School of Electronics Engineering and Computer Science Peking University Frontiers Science Center for Nano-optoelectronics Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(iMLic) Department of Electronic Engineering Shanghai Jiao Tong University

Brain-inspired photonic neural networks for artificial intelligence have attracted renewed interest. For many computational tasks, such as image recognition, speech processing and deep learning, photonic neural networks have the potential to increase the computing speed and energy efficiency on the orders of magnitude compared with digital electronics. Silicon Photonics, which combines the advantages of electronics and photonics, brings hope for the large-scale photonic neural network integration. This paper walks through the basic concept of artificial neural networks and focuses on the key devices which construct the silicon photonic neuromorphic systems. We review some recent important progress in silicon photonic neural networks, which include multilayer artificial neural networks and brain-like neuromorphic systems, for artificial intelligence. A prototype of silicon photonic artificial intelligence processor for ultra-fast neural network computing is also proposed. We hope this paper gives a detailed overview and a deeper understanding of this emerging field.

关键词： photonic neural networks artificial intelligence deep learning photonic computing accelerator silicon photonics

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Accelerated primal-dual mirror dynamics for centralized and distributed constrained convex optimization problems

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2023年第1期24卷 16413-16471页

作者： You Zhao Xiaofeng Liao Xing He Mingliang Zhou Chaojie Li College of Electronic and Information Engineering Southwest University Chongqing PR. China College of Computer Science Chongqing University Chongqing PR. China State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power University Beijing China

This paper investigates two accelerated primal-dual mirror dynamical approaches for smooth and nonsmooth convex optimization problems with afine and closed, convex set constraints. In the smooth case, an accelerated primal-dual mirror dynamical approach (APDMD) based on accelerated mirror descent and primal-dual framework is proposed and accelerated convergence properties of primal-dual gap, feasibility measure and the objective function value along with trajectories of APDMD are derived by the Lyapunov analysis method. Then, we extend APDMD into two distributed dynamical approaches to deal with two types of distributed smooth optimization problems, i.e., distributed constrained consensus problem (DCCP) and distributed extended monotropic optimization (DEMO) with accelerated convergence guarantees. Moreover, in the nonsmooth case, we propose a smoothing accelerated primal-dual mirror dynamical approach (SAPDMD) with the help of smoothing approximation technique and the above APDMD. We further also prove that primal-dual gap, objective function value and feasibility measure along with trajectories of SAPDMD have the same accelerated convergence properties as APDMD by choosing the appropriate smooth approximation parameters. Later, we propose two smoothing accelerated distributed dynamical approaches to deal with nonsmooth DEMO and DCCP to obtain accelerated and efficient solutions. Finally, numerical and comparative experiments are given to demonstrate the effectiveness and superiority of the proposed accelerated mirror dynamical approaches.

关键词： machine learning accelerated mirror dynamical approaches constrained smooth and nonsmooth convex optimization smoothing approximation distributed approaches

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Intelligent Energy-Efficient Resource Allocation for Multi-UAV-Assisted Mobile Edge Computing Networks

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China Communications 2025年第4期22卷 339-355页

作者： Hu Han Shen Le Zhou Fuhui Wang Qun Zhu Hongbo The China Information Consulting and Designing Institute CO. Ltd.Nanjing 210000China The Jiangsu Key Laboratory of Wireless Communications(Nanjing University of Posts and Telecommunications) Nanjing 210003China The Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Ministry of Education(Nanjing University of Posts and Telecommunications)Nanjing 210003China The College of Artificial Intelligence(Nanjing University of Aeronautics and Astronautics) Nanjing 210000China The Department of Computer Science(San Francisco State University) San FranciscoCAUSA

The unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)has been deemed a promising solution for energy-constrained devices to run smart applications with computationintensive and latency-sensitive requirements,especially in some infrastructure-limited areas or some emergency ***,the multi-UAVassisted MEC network remains largely *** this paper,the dynamic trajectory optimization and computation offloading are studied in a multi-UAVassisted MEC system where multiple UAVs fly over a target area with different trajectories to serve ground *** considering the dynamic channel condition and random task arrival and jointly optimizing UAVs'trajectories,user association,and subchannel assignment,the average long-term sum of the user energy consumption minimization problem is *** address the problem involving both discrete and continuous variables,a hybrid decision deep reinforcement learning(DRL)-based intelligent energyefficient resource allocation and trajectory optimization algorithm is proposed,named HDRT algorithm,where deep Q network(DQN)and deep deterministic policy gradient(DDPG)are invoked to process discrete and continuous variables,*** results show that the proposed HDRT algorithm converges fast and outperforms other benchmarks in the aspect of user energy consumption and latency.

关键词： dynamic trajectory optimization intelligent resource allocation unmanned aerial vehicle uav assisted uav assisted mec energy efficiency smart applications mobile edge computing mec deep reinforcement learning

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Collaborative Perception Datasets for Autonomous Driving: A Review

arXiv

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arXiv 2025年

作者： Wang, Naibang Shang, Deyong Gong, Yan Hu, Xiaoxi Song, Ziying Yang, Lei Huang, Yuhan Wang, Xiaoyu Lu, Jianli Beijing100083 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China State Key Laboratory of Intelligent Green Vehicle and Mobility Tsinghua University Beijing100084 China Beijing Key Laboratory of Traffic Data Mining and Embodied Intelligence School of Computer Science and Technology Beijing Jiaotong University China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore School of Mechatronics Engineering Harbin Institute of Technology 92 West Dazhi St. Harbin China Department of Electronic & Electrical Engineering University of Bath United Kingdom

Collaborative perception has attracted growing interest from academia and industry due to its potential to enhance perception accuracy, safety, and robustness in autonomous driving through multi-agent information fusion. With the advancement of Vehicle-to-Everything (V2X) communication, numerous collaborative perception datasets have emerged, varying in cooperation paradigms, sensor configurations, data sources, and application scenarios. However, the absence of systematic summarization and comparative analysis hinders effective resource utilization and standardization of model evaluation. As the first comprehensive review focused on collaborative perception datasets, this work reviews and compares existing resources from a multi-dimensional perspective. We categorize datasets based on cooperation paradigms, examine their data sources and scenarios, and analyze sensor modalities and supported tasks. A detailed comparative analysis is conducted across multiple dimensions. We also outline key challenges and future directions, including dataset scalability, diversity, domain adaptation, standardization, privacy, and the integration of large language models. To support ongoing research, we provide a continuously updated online repository of collaborative perception datasets and related literature: https://***/frankwnb/Collaborative-Perceptio n-Datasets-for-Autonomous-Driving. © 2025, CC BY-SA.

关键词： Sensor data fusion

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Sparse Channel Reconstruction: A Generative Adversarial Network-Based Approach

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IEEE Transactions on Cognitive Communications and Networking 2024年

作者： Zhang, Yuxin He, Ruisi Yang, Mi Wang, Chenlong Qiu, Zhicheng Lu, Yang Ai, Bo Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation The Frontiers Science Center for Smart High-speed Railway System Beijing100044 China Beijing Jiaotong University School of Computer and Information Technology Beijing100044 China

Wireless channels typically exhibit a sparse structure, with sparsity regarded as an inherent characteristics. A deeper understanding and accurate representation of channel sparsity contribute to a more comprehensive revelation of channel features and structure, thereby enhancing the performance of communication systems. However, current research on channel sparsity remains limited to the measurement, and traditional channel models have not sufficiently incorporated this critical characteristic. In this paper, considering channel deep sparse characteristics, a generative adversarial network (GAN)-based channel sparsity-tunable framework is proposed to reconstruct channel samples with various levels of sparsity. Specifically, continuous sparsity factors and a sparsity measurement module are introduced to manipulate and predict the sparsity of the reconstructed channel in the framework design. Channel power and delay are employed for model training to better consider the channel behavior of sparsity. Furthermore, the mutual information between input sparsity factors and reconstructed channels is enhanced to ensure that the sparsity factor has an actual impact on the level of reconstructed channel sparsity, thereby enabling the flexible and continuous reconstruction of channels with varying levels of sparsity. Simulation results prove that the proposed framework can effectively and accurately reconstruct channels with different levels of sparsity by changing sparsity factor, as well as providing good performance in measuring the sparsity of wireless channel. Finally, sparse manipulation performance is further validated using channel capacity simulation. © 2024 IEEE.

关键词： Signal reconstruction

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Validating SMT Solvers via Skeleton Enumeration Empowered by Historical Bug-Triggering Inputs

Validating SMT Solvers via Skeleton Enumeration Empowered by...

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International Conference on Software Engineering (ICSE)

作者： Maolin Sun Yibiao Yang Ming Wen Yongcong Wang Yuming Zhou Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology China Hubei Key Laboratory of Distributed System Security Services Computing Technology and System Lab Cluster and Grid Computing Lab Hubei Engineering Research Center on Big Data Security National Engineering Research Center for Big Data Technology and System State Key Laboratory for Novel Software Technology Nanjing University China School of Computer Science and Technology Huazhong University of Science and Technology China

SMT solvers check the satisfiability of logic formulas over first-order theories, which have been utilized in a rich number of critical applications, such as software verification, test case generation, and program synthesis. Bugs hidden in SMT solvers would severely mislead those applications and further cause severe consequences. Therefore, ensuring the reliability and robustness of SMT solvers is of critical importance. Although many approaches have been proposed to test SMT solvers, it is still a challenge to discover bugs effectively. To tackle such a challenge, we conduct an empirical study on the historical bug-triggering formulas in SMT solvers' bug tracking systems. We observe that the historical bug-triggering formulas contain valuable skeletons (i.e., core structures of formulas) as well as associated atomic formulas which can cast significant impacts on formulas' ability in triggering bugs. Therefore, we propose a novel approach that utilizes the skeletons extracted from the historical bug-triggering formulas and enumerates atomic formulas under the guidance of association rules derived from historical formulas. In this study, we realized our approach as a practical fuzzing tool HistFuzz and conducted extensive testing on the well-known SMT solvers Z3 and cvc5. To date, HistFuzz has found 111 confirmed new bugs for Z3 and cvc5, of which 108 have been fixed by the developers. More notably, out of the confirmed bugs, 23 are soundness bugs and invalid model bugs found in the solvers' default mode, which are essential for SMT solvers. In addition, our experiments also demonstrate that HistFuzz outperforms the state-of-the-art SMT solver fuzzers in terms of achieved code coverage and effectiveness.

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Communication Network Selection for Distribution Network Based on Analytic Hierarchy Process

Communication Network Selection for Distribution Network Bas...

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Power Engineering Application (ICPEA), IEEE International Conference in

作者： Wei Ge Qi Wei Weijun Hong Yuchen Wu Cui Li Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China State Grid Economic and Technological Research Institute CO. LTD Beijing China Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China State Grid Fujian Economic Research Institute Fuzhou China

The access of large-scale distributed new energy has high requirements for the protection of new distribution network and communication network, but the selection of the communication network has no definite standard. In this paper, a communication network selection mechanism based on Analytic Hierarchy Process (AHP) is proposed to solve the problem of smart grid communication network selection. This method is based on the principle of decision-making analysis combining qualitative and quantitative analysis of multi- objective complex problems. The weight of indexes at all levels are calculated by the judgment matrix. After the consistency test, the overall judgment matrix is calculated to select the best scheme, which achieves the effect of decomposing and analyzing the communication network of distribution network. Through the analysis of 5 kinds of communication networks, namely optical fiber communication network, 4G network, 5G network, wireless private network and power line carrier, this research constructs the AHP model with accessibility, coverage, economy, reliability and security as the main parameter indexes, and obtains that 5G is the optimal scheme with 26.0178% of the comprehensive weight. Therefore, 5G network is more suitable for the application in the distribution network under the current new energy access.

关键词： Wireless communication 5G mobile communication Distribution networks Optical fiber communication Smart grids Communication networks Security

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