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2025 IEEE International Conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Li, Zhongyang Yuan, Xin Liu, Wei Xu, Xin School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System China

ISBN: (纸本)9798350368741

Cross-view object geo-localization (CVOGL) aims to locate an object of interest in a captured ground- or drone-view image within the satellite image. However, existing works treat ground-view and drone-view query images equivalently, overlooking their inherent viewpoint discrepancies and the spatial correlation between the query image and the satellite-view reference image. To this end, this paper proposes a novel View-specific Attention Geo-localization method (VAGeo) for accurate CVOGL. Specifically, VAGeo contains two key modules: view-specific positional encoding (VSPE) module and channel-spatial hybrid attention (CSHA) module. In object-level, according to the characteristics of different viewpoints of ground and drone query images, viewpoint-specific positional codings are designed to more accurately identify the click-point object of the query image in the VSPE module. In feature-level, a hybrid attention in the CSHA module is introduced by combining channel attention and spatial attention mechanisms simultaneously for learning discriminative features. Extensive experimental results demonstrate that the proposed VAGeo gains a significant performance improvement, i.e., improving acc@0.25/acc@0.5 on the CVOGL dataset from 45.43%/42.24% to 48.21%/45.22% for ground-view, and from 61.97%/57.66% to 66.19%/61.87% for drone-view. © 2025 IEEE.

关键词： Cross-view Object-level Localization Hybrid Attention Mechanism View-specific Positional Encoding

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Day-ahead Chance-constrained Energy Management of Energy Hubs:A Distributionally Robust Approach

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CSEE Journal of Power and Energy systems 2022年第3期8卷 812-825页

作者： Jiaxin Cao Bo Yang Shanying Zhu Chao Ning Xinping Guan Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing Ministry of Education of China Robert Frederick Smith School of Chemical and Biomolecular Engineering Cornell UniversityIthacaNY 14853 USA

The day-ahead management schedules of hybrid energy hubs are intricate and usually exposed to various uncertainties with the penetration of renewable sources and different ***,it is difficult to access to precise probability distribution functions and exact moment information of uncertain *** cope with these issues,an energy management scheme based on the distributionally robust optimization approach is developed for the energy *** makes no assumptions of certain probability distributions and can be implemented with limited empirical data and partial information of underlying *** operational strategy can provide decision makers with a preliminary and robust optimal solution in the day-ahead *** results illustrate the economical benefit of the energy model,and the effectiveness of the proposed approach in chance-constrained energy management is demonstrated by comparing with other *** Terms-Chance constraint,distributionally robust optimization,energy hub,energy management.

关键词： Chance constraint distributionally robust optimization energy hub energy management

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HPHR-SAR-Net: Hyperpixel High-Resolution SAR Imaging Network Based on Nonlocal Total Variation

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2023年 16卷 8595-8608页

作者： Zhou, Guoru Xu, Zhongqiu Fan, Yizhe Zhang, Zhe Qiu, Xiaolan Zhang, Bingchen Fu, Kun Wu, Yirong Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing100045 China University of Chinese Academy of Sciences Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100045 China Suzhou Aerospace Information Research Institute Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Suzhou215009 China

High resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. First, these algorithms tend to focus on local information, neglecting nonlocal information between different pixel patches. Second, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Third, the process of high-resolution SAR imaging generally involves high time and computational complexity, making real-time imaging difficult to achieve. To address these issues, we propose a hyperpixel high-resolution SAR imaging network (HPHR-SAR-Net) for rapid despeckling in high-resolution modes. Based on the concept of hyperpixel techniques, we initially combine nonconvex and nonlocal total variation as compound regularization. This approach more effectively despeckles and manages the relationship between pixels while reducing bias effects caused by convex constraints. Subsequently, we solve the compound regularization model using the alternating direction method of multipliers (ADMM) algorithm and unfold it into a deep unfolding network (DUN). The network's parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the proposed HPHR-SAR-Net is compatible with high-resolution imaging modes, such as spotlight, staring spotlight, and sliding spotlight. In this article, we demonstrate the superiority of HPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that HPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results. © 2008-2012 IEEE.

关键词： Radar imaging

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An Enhanced Particle Swarm Algorithm Based on Fitness Landscape information 13

An Enhanced Particle Swarm Algorithm Based on Fitness Landsc...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Diao, Zhenya Yu, Fei Guan, Jian Liu, Meitong School of Physics and Information Engineering Minnan Normal University Key Lab of Intelligent Optimization and Information Processing Zhangzhou36300 China School of Physics and Information Engineering Minnan Normal University Key Laboratory of Light Field Manipulation and System Integration Applications in Fujian Province Key Lab of Intelligent Optimization and Information Processing Zhangzhou36300 China

ISBN: (纸本)9798350308365

In the original Particle Swarm Optimization (PSO), the selection of parameters significantly impacts the search capability of PSO. The paper introduces an innovative algorithm called Fitness Landscape-based PSO (FLPSO) to address the impact of parameter selection on the search capability of PSO. The algorithm focuses on acquiring fitness landscape information and analyzing the population state to intelligently select appropriate parameters in each generation. FLPSO defines four primary states: exploration, exploitation, convergence, and escaping state. In the convergence state, an elite learning strategy is incorporated to help the algorithm escape potential local optima by targeting the global best particle. To validate the efficacy of FLPSO, the paper conducted experiments on 30 different characteristic test functions from CEC2017. FLPSO was compared with six existing algorithms: PSO, PSO-TVAC, APSO, AWPSO, RPSO and ASRPPSO. The experimental results showed significant improvements in FLPSO, providing promising evidence for its effectiveness. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Data secure transmission intelligent prediction algorithm for mobile industrial IoT networks

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Digital Communications and Networks 2023年第2期9卷 400-410页

作者： Lingwei Xu Hao Yin Hong Jia Wenzhong Lin Xinpeng Zhou Yong Fu Xu Yu Department of Information Science and Technology Qingdao University of Science and TechnologyQingdao266061China Fujian Key Laboratory of Sensing and Computing for Smart Cities Xiamen UniversityXiamen361005China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control(Minjiang University) Fuzhou350121China Faculty of Information Science and Engineering Ocean University of ChinaQingdao266100China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center(National Supercomputer Center in Jinan)JinanChina

Mobile Industrial Internet of Things(IIoT)applications have achieved the explosive growth in recent *** mobile IIoT has flourished and become the backbone of the industry,laying a solid foundation for the interconnection of all *** variety of application scenarios has brought serious challenges to mobile IIoT networks,which face complex and changeable communication *** data secure transmission is critical for mobile IIoT *** paper investigates the data secure transmission performance prediction of mobile IIoT *** cut down computational complexity,we propose a data secure transmission scheme employing Transmit Antenna Selection(TAS).The novel secrecy performance expressions are first ***,to realize real-time secrecy analysis,we design an improved Convolutional Neural Network(CNN)model,and propose an intelligent data secure transmission performance prediction *** mobile signals,the important features may be removed by the pooling *** will lead to negative effects on the secrecy performance prediction.A novel nine-layer improved CNN model is *** of the input and output layers,it removes the pooling layer and contains six convolution ***,Back-Propagation(BP)and LeNet methods are employed to compare with the proposed *** simulation analysis,good prediction accuracy is achieved by the CNN *** prediction accuracy obtains a 59%increase.

关键词： Mobile IIoT networks Data secure transmission Performance analysis Intelligent prediction Improved CNN

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A Cross-Multi-Domain Trust Assessment Authority Delegation Method Based on Automotive Industry Chain

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Computers, Materials & Continua 2025年第1期82卷 407-426页

作者： Binyong Li Liangming Deng Jie Zhang Xianhui Deng School of Cybersecurity(Xin Gu Industrial College) Chengdu University of Information TechnologyChengdu610225China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225China SUGON Industrial Control and Security Center Chengdu610225China

To solve the challenges of connecting and coordinating multiple platforms in the automotive industry and to enhance collaboration among different participants,this research focuses on addressing the complex supply relationships in the automotive market,improving data sharing and interactions across various platforms,and achieving more detailed integration of data and *** propose a trust evaluation permission delegation method based on the automotive industry *** proposed method combines smart contracts with trust evaluation mechanisms,dynamically calculating the trust value of users based on the historical behavior of the delegated entity,network environment,and other factors to avoid malicious node attacks during the permission delegation *** also introduce strict control over the cross-domain permission granting and revocation mechanisms to manage the delegation path,prevent information leakage caused by malicious node interception,and effectively protect data integrity and *** analysis shows that this method meets the realtime requirements of collaborative interaction in the automotive industry chain and provides a feasible solution to permission delegation issues in the automotive industry chain,offering dynamic flexibility in authorization and scalability compared to most existing solutions.

关键词： Automotive industry chain cross-domain access block chain delegate authority trust assessment

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Triggered Mechanism for Strict Feedback systems under Unknown control Directions 14

Triggered Mechanism for Strict Feedback Systems under Unknow...

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14th Asian control Conference, ASCC 2024

作者： Liu, Guilong Wu, Hongda Yang, Yongliang Xie, Wei Zhang, Weidong School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581598

This paper presents an event-based asymptotic tracking control scheme designed for strict feedback systems with unknown control directions. The control directions directly determine how the controller acts on the system, thus impacting the system's stability and convergence speed. When the control directions are unknown, it presents a significant challenge in controller design. To tackle this issue, the Nussbaum-type gains are introduced. However, this method increases communication overhead. Hence, an event-triggered mechanism is introduced to alleviate this burden. Additionally, to achieve and maintain desired target states, satisfying control requirements and performance demands, this paper improves the event-triggered mechanism to achieve asymptotic tracking. Finally, the feasibility and effectiveness of the proposed design are validated through a simulation example. © 2024 Asian control Association.

关键词： Feedback

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Generic Software Design for Radar Basic Data Inspection

Generic Software Design for Radar Basic Data Inspection

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2024 Advanced Fiber Laser Conference, AFL 2024

作者： Chen, HongLi Fu, JianChuan Liu, RenJie Ding, Chao Wang, Mingyang Key Laboratory of Information System and Technology Beijing Institute of Control and Electronic Technology No. 51 North Muxidi Xicheng District Beijing100038 China

ISBN: (数字)9781510688889

ISBN: (纸本)9781510688872

A general data inspection software based on the basic data of multi-source radar was designed, which was the central part of the data pre-processing. In this paper, software requirements analysis, overall architecture design, workflow design and detailed function design were carried out. Detailed functions included radar basic data loading, data analysis and recombination, data inspection requirement analysis, preprocessing model loading and data inspection. Data checks included normalization, completeness, correctness, consistency, current status, and satisfaction. Eventually, the software can present the results of the data inspection in the form of visualizations or reports. This software provided more general radar data review and filtering services. © 2025 SPIE.

关键词： Inspection Data modeling Radar Design Databases Data processing Statistical analysis Data acquisition Data storage Reliability

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H∞ Model Reduction for Takagi-Sugeno Fuzzy systems via Space Projection 48

H∞ Model Reduction for Takagi-Sugeno Fuzzy Systems via Spac...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Zheng, Hua Zou, Yuanyuan Li, Shaoyuan Shanghai Jiao Tong University Ministry of Education Key Laboratory of System Control and Information Processing Department of Automation Shanghai China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

In this paper, the problem of model reduction for Takagi-Sugeno (T-S) fuzzy systems is studied. The virtual inner disturbance is first constructed to map a potential link between the states of two systems before and after dimensionality reduction. Based on Lyapunov theorem, the H∞ approach is then used to analyze the augmented system with the inner disturbance. The results are unrelated to reduced-order system membership functions (MFs), which can be freely selected. Furthermore, both the number of rules and the size of the reduced-order system and the inner disturbance may be flexibly chosen. An example is adapted to demonstrate the efficiency of the proposed method. © 2022 IEEE.

关键词： Membership functions

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Energy-Efficient Driving Strategy for High-Speed Trains with Considering the Checkpoints

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Chinese Journal of Electronics 2024年第3期33卷 847-858页

作者： Zixuan ZHANG Yuan CAO Shuai SU State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University School of Electronic and Information Engineering Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University

With rising energy prices and concerns about environmental issues,energy-efficient driving strategies(EEDS) for high-speed trains have received a substantial amount of *** particular,energy-saving schemes play a huge role in reducing the energy and operating costs of *** article studies the EEDS of high-speed trains at a given time.A well-posed model is formulated,in which the constraints of the checkpoints,in addition to the speed limits,vehicle dynamics,and discrete control throttle,are first *** a given control sequence,the Karush-Kuhn-Tucker(KKT) conditions are used to obtain the necessary conditions for an *** to several key equations of the necessary conditions,the checkpoint constraints are *** case studies are conducted based on the data of the Beijing-Shanghai high-speed line to illustrate the effectiveness of the proposed approach.

关键词： Energy-efficiency High-speed trains Checkpoints

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