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HIET:Hybrid Information Enhancement Transformer Network for Single-Photon Image Reconstruction

Journal of beijing Institute of technology 2025年第1期34卷 1-17页

作者： Yiming Liu Xuri Yao Tao Zhang Yifei Sun Ying Fu School of Computer Science and Technology Beijing Institute of TechnologyBeijing 100081China Center for Quantum Technology Research and Key Laboratory of Advanced Optoelec-tronic Quantum Architecture and Measurements(MOE) School of PhysicsBeijing Institute of TechnologyBeijing 100081China School of Communication Engineering Hangzhou Dianzi UniversityHangzhou 310018China Uniview Technology Hangzhou 310056China

Single-photon sensors are novel devices with extremely high single-photon sensitivity and temporal ***,these advantages also make them highly susceptible to ***,single-photon cameras face severe quantization as low as 1 bit/*** factors make it a daunting task to recover high-quality scene information from noisy single-photon *** current image reconstruction methods for single-photon data are mathematical approaches,which limits information utilization and algorithm *** this work,we propose a hybrid information enhancement model which can significantly enhance the efficiency of information utilization by leveraging attention mechanisms from both spatial and channel ***,we introduce a structural feature enhance module for the FFN of the transformer,which explicitly improves the model's ability to extract and enhance high-frequency structural information through two symmetric convolution ***,we propose a single-photon data simulation pipeline based on RAW images to address the challenge of the lack of single-photon *** results show that the proposed method outperforms state-of-the-art methods in various noise levels and exhibits a more efficient capability for recovering high-frequency structures and extracting information.

关键词： single-photon images hybrid information enhancement structual feature enhancement data simulation pipeline

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Breaking demodulation limitations:AWG and Deep Learning in Dynamic Spectral Reconstruction for Differential FBG Accelerometers

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IEEE Sensors Journal 2025年第11期25卷 19210-19222页

作者： Yang, Qian Liu, Lei Niu, Ning Quan, ChenYi Ren, SuFen Chen, ShengChao Zhang, JiaLin Yan, YuMeng Xiang, LongTeng Wang, YiPing Liao, ChangRui He, Jun Wang, GuanJun School of Information and Communication Engineering Hainan University College of Electronic Science and Technology China Henan Mechanical and Electrical Vocational College School of Electrical Engineering Henan451100 China Hainan University College of Electronic Science and Technology School of Information and Communication Engineering Haikou570228 China University of Technology Sydney School of Computer Science Faculty of Engineering and Information Technology SydneyNSW Australia Hainan University College of Electronic Science and Technology Haikou570228 China Shenzhen University School of Physics and Optoelectronic Engineering Shenzhen518060 China

Conventional fiber Bragg grating (FBG) accelerometer demodulation often suffers from high environmental sensitivity, complexity, and cost. To address these issues, this paper presents two arrayed waveguide grating (AWG)-based dynamic spectral reconstruction models. First, a novel differential FBG accelerometer with an equal-intensity triangular cantilever beam and a symmetric string-like design enhances sensitivity and mitigates temperature interference. A power ratio-nonlinear logarithmic regression (PR-NLR) model derived from static calibration then enables spectral reconstruction and wavelength demodulation across varying accelerations, achieving 4-82pm accuracy, slightly below that of high-speed demodulators (HSD). Next, by integrating convolutional neural networks (CNN), bidirectional long short-term memory (BiLSTM), attention mechanisms, and a generative adversarial network (GAN) for data augmentation, prediction errors drop to 1-26pm at 20Hz and 0.2-21pm at 40Hz-a reduction of at least 60% over PR-NLR. This outcome underscores the advantages of deep learning (DL) in managing complex spectral shifts. By overcoming frequency-only demodulation limits, the proposed AWG approach achieves precise wavelength demodulation through dynamic spectral reconstruction. Its compact design, low manufacturing cost, and robust performance facilitate scalable deployment in structural health monitoring, particularly for bridge vibration analysis and industrial machinery diagnostics. © 2001-2012 IEEE.

关键词： Arrayed waveguide gratings

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A Novel Construction of Two-Dimensional Z-Complementary Array Code Sets Based on Extended Boolean Functions

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IEEE Transactions on Vehicular technology 2025年第5期74卷 7821-7834页

作者： Tian, Liying Song, Xiaoshi Li, Yubo Zhang, Haijun Northeastern University School of Computer Science and Engineering Shenyang110819 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110189 China Yanshan University School of Information Science and Engineering Qinhuangdao066004 China Hebei Key Laboratory of Information Transmission and Signal Processing Qinhuangdao066004 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China

Two-dimensional (2-D) array sets with good 2-D correlation properties have received considerable attention in wireless communication systems. This paper focuses on 2-D Z-complementary array code sets (ZCACSs), which have ideal 2-D correlation properties within a rectangular zone around the origin. By developing a theory linking 2-D extended Boolean functions with 2-D arrays, we establish an efficient construction of 2-D ZCACSs. In contrast to previous work, the proposed construction is capable of producing 2-D ZCACSs with new flexible parameters. Constructions of three-dimensional (3-D) and higher-dimensional ZCACSs are further investigated. We remark that 2-D and higher-dimensional complete complementary codes (CCCs) can also be generated from the proposed constructions. © 1967-2012 IEEE.

关键词： Codes (symbols)

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Blockchain-Based Trust Model for Inter-Domain Routing

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computers, Materials & Continua 2025年第3期82卷 4821-4839页

作者： Qiong Yang Li Ma Sami Ullah Shanshan Tu Hisham Alasmary Muhammad Waqas Faculty of Information Technology Beijing University of TechnologyBeijing100124China School of Information Science and Technology North China University of TechnologyBeijing100144China Department of Computer Science Shaheed Benazir Bhutto UniversitySheringal18050Pakistan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia School of Computing andMathematical Sciences Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUK School of Engineering Edith Cowan UniversityPerthWA 6027Australia

Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,communicating in a distributed dynamic environment,face several security challenges,with trust being one of the most important issues in inter-domain *** research,which performs trust evaluation when exchanging routing information to suppress malicious routing behavior,cannot meet the scalability requirements of BGP *** this paper,we propose a blockchain-based trust model for inter-domain *** model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the *** BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective *** incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing *** forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing *** use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust *** with the classical trust model,our trust model not only saves more storage overhead,but also provides higher security,especially reducing the impact of collusion attacks.

关键词： Inter-domain routing BGP security blockchain trust model trust mechanisms trust evaluation

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An overview on IRS-enabled sensing and communications for 6G: architectures, fundamental limits, and joint beamforming designs

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science China(Information sciences) 2025年第5期68卷 170-193页

作者： Xianxin SONG Yuan FANG Feng WANG Zixiang REN Xianghao YU Ye ZHANG Fan LIU Jie XU Derrick Wing Kwan NG Rui ZHANG Shuguang CUI School of Science and Engineering (SSE) Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen)and Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Department of Electrical Engineering City University of Hong Kong School of Information Engineering Guangdong University of Technology Key Laboratory of Wireless-Optical Communications Chinese Academy of Sciences School of Information Science and Technology University of Science and Technology of China Computer School Beijing Information Science and Technology University National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University School of Electrical Engineering and Telecommunications University of New South Wales School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Department of Electrical and Computer Engineering National University of Singapore

This study presents an overview on intelligent reflecting surface(IRS)-enabled sensing and communication for the forthcoming sixth-generation(6G) wireless networks, in which IRSs are strategically deployed to proactively reconfigure wireless environments to improve both sensing and communication(S&C) performance. First, we exploit a single IRS to enable wireless sensing in the base station's(BS's) non-line-of-sight(NLoS) area. In particular, we present three IRS-enabled NLoS target sensing architectures with fully-passive, semi-passive, and active IRSs, respectively. We compare their pros and cons by analyzing the fundamental sensing performance limits for target detection and parameter estimation. Next, we consider a single IRS to facilitate integrated sensing and communication(ISAC), in which the transmit signals at the BS are used for achieving both S&C functionalities, aided by the IRS through reflective beamforming. We present joint transmit signal and receiver processing designs for realizing efficient ISAC, and jointly optimize the transmit beamforming at the BS and reflective beamforming at the IRS to balance the fundamental performance tradeoff between S&C. Furthermore, we discuss multi-IRS networked ISAC, by particularly focusing on multi-IRS-enabled multi-link ISAC, multi-region ISAC, and ISAC signal routing, respectively. Finally, we highlight various promising research topics in this area to motivate future work.

关键词： integrated sensing and communication (ISAC) intelligent reflecting surface (IRS) non-line-of-sight (NLoS) sensing sensing and communication tradeoff

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Study on flood probability by neural network prediction based on the importance of random forest characteristics 3

Study on flood probability by neural network prediction base...

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3rd International Conference on Electrical, Electronics, and Information engineering, EEIE 2024

作者： Zhang, Yujun Kang, Yu Liu, Yupeng Fan, Rulong Duan, Jianfu School of Computer Science and Technology Taiyuan University of Science and Technology China School of Information and Communication Engineering Beijing University of Posts and Telecommunications China School of Economics and Management Taiyuan University of Technology China

ISBN: (纸本)9781510688179

In recent years, global climate change and human activities have intensified the frequency and severity of floods. Based on the big data of flood probability, combined with the index data of monsoon intensity, river management, deforestation, urbanization and climate change, this paper studies from the perspective of flood probability prediction. Firstly, this paper selects indicators and collects corresponding data, and processes the data. Then, the importance of index characteristics is evaluated by the random forest algorithm. Secondly, the number of final indicators is determined by kernel principal component analysis, and the final indicators are determined by combining the importance of features. Then, the number of classifications is determined by the AIC/BIC criterion, and the risk is classified into three categories: high, medium, and low, by GMM clustering, based on the EM algorithm. Finally, 60% of the data is used as the training set, 30% of the data as the verification set, and 10% of the data as the test set to divide the data set, and then it is brought into the neural network prediction model for prediction. Finally, by analyzing the clustering results and prediction results, it provides a scientific basis and a practical application scheme for disaster prevention and reduction. © The Authors.

关键词： Flood damage

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Energy Oriented Three-Tier Computation Offloading Scheme in Maritime Edge Computing Network

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IEEE Transactions on Vehicular technology 2025年第5期74卷 8126-8140页

作者： Zhang, Hongxia Xi, Shiyu Shang, Bodong Zhang, Peiying Wu, Sheng Jiang, Chunxiao Qingdao Institute of Software College of Computer Science and Technology Qingdao266580 China Eastern Institute of Technology Eastern Institute for Advanced Study Ningbo315200 China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China

With the development of maritime continuing to grow, large-scale maritime wireless devices (MWDs) are being deployed for various maritime applications. The rapid development of maritime Internet of Things (IoT) and growing demand for these applications have led to an increasing number of computation-intensive and resource-sensitive tasks. Considering the limited computing capacity and energy of MWDs, it is challenging to transmit and process massive maritime computing tasks in an energy efficient manner. In this paper, we propose a three-tier maritime edge computing system in which low earth orbit (LEO) satellite and offshore base station (OBS) support to provide communication and computing services for MWDs. The system optimizes association variable, task partitioning, transmission power, and computing resource allocation to reduce system energy consumption under latency constraints. The optimization problem is formulated as a mixed integer non-linear programming (MINLP) optimization problem. We decompose the original problem into four subproblems and design algorithms to solve them. Firstly, the association variable optimization subproblem is solved by slack variable method. Then, we adopt quadratic transformation and design a difference of convex algorithm to solve transmission power optimization subproblem. Further, task partitioning subproblem is solved by obtaining upper and lower bounds of offloading task size by strict deduction, and then solved by the standard convex method. Finally, Lagrangian dual method is utilized to deal with joint computing resource optimization subproblem of LEO satellite and OBS. In simulation results, the proposed algorithm saves 39.3% of system energy consumption compared to benchmark schemes. © 1967-2012 IEEE.

关键词： Computation offloading

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Exploring Dynamics and Hardware Implementation of an Enhanced 5D Hyperchaotic Memristive System Inspired by Sprott-C System

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Complex System Modeling and Simulation 2025年第1期5卷 34-45页

作者： Mokbel, Abdulmajeed Abdullah Mohammed Yu, Fei Gracia, Yumba Musoya Tan, Bohong Lin, Hairong Iu, Herbert Ho-Ching School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China School of Electronic Information Central South University Changsha410083 China School of Electrical Electronic and Computer Engineering University of Western Australia Perth6009 Australia

This paper proposes a novel 5D hyperchaotic memristive system based on the Sprott-C system configuration, which greatly improves the complexity of the system to be used for secure communication and signal processing. A critical aspect of this research work is the introduction of a flux-controlled memristor that exhibits chaotic behavior and dynamic responses of the system. To this respect, detailed mathematical modeling and numerical simulations about the stability of the system's equilibria, bifurcations, and hyperchaotic dynamics were conducted and showed a very wide variety of behaviors of great potential in cryptographic applications and secure data transmission. Then, the flexibility and efficiency of the real-time operating environment were demonstrated, and the system was actually implemented on a field-programmable gate array (FPGA) hardware platform. A prototype that confirms the theoretical framework was presented, providing new insights for chaotic systems with practical significance. Finally, we conducted National Institute of Standards and technology (NIST) testing on the proposed 5D hyperchaotic memristive system, and the results showed that the system has good randomness. © 2021 TUP.

关键词： Digital storage

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FDCPNet:feature discrimination and context propagation network for 3D shape representation

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虚拟现实与智能硬件(中英文) 2025年第1期7卷 83-94页

作者： Weimin SHI Yuan XIONG Qianwen WANG Han JIANG Zhong ZHOU State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Background Three-dimensional(3D)shape representation using mesh data is essential in various applications,such as virtual reality and simulation *** methods for extracting features from mesh edges or faces struggle with complex 3D models because edge-based approaches miss global contexts and face-based methods overlook variations in adjacent areas,which affects the overall *** address these issues,we propose the Feature Discrimination and Context Propagation Network(FDCPNet),which is a novel approach that synergistically integrates local and global features in mesh *** FDCPNet is composed of two modules:(1)the Feature Discrimination Module,which employs an attention mechanism to enhance the identification of key local features,and(2)the Context Propagation Module,which enriches key local features by integrating global contextual information,thereby facilitating a more detailed and comprehensive representation of crucial areas within the mesh *** Experiments on popular datasets validated the effectiveness of FDCPNet,showing an improvement in the classification accuracy over the baseline ***,even with reduced mesh face numbers and limited training data,FDCPNet achieved promising results,demonstrating its robustness in scenarios of variable complexity.

关键词： 3D shape representation Mesh model MeshNet Feature discrimination Context propagation

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DSCCNet for high-quality 4K computer-generated holograms

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Optics Express 2025年第6期33卷 13733-13747页

作者： Xu, Zhenqi Leng, Junmin Dai, Ping Wang, Chao Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing100101 China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100101 China School of Information and Communications Engineering Beijing Information Science and Technology University Beijing100101 China

With the increasing demand for high-quality 3D holographic reconstruction, visual clarity and accuracy remain significant challenges in various imaging applications. Current methods struggle for higher image resolution and to resolve such issues as detail loss and checkerboard artifacts. To address these challenges, we propose the model Depthwise Separable Complex-valued Convolutional Network (DSCCNet) for phase-only computer-generated holography (CGH). This deep learning framework integrates complex-valued convolutions with depthwise separable convolutions to enhance reconstruction precision and improve model training efficiency. Additionally, the diffuser is employed to reduce checkerboard artifacts in defocused parts of 3D CGH. Experimental results demonstrate that DSCCNet can obtain 4K images reconstructed with more intricate details. The reconstruction quality of both 2D and 3D layered objects is enhanced. Validation on 100 images from the DIV2K dataset shows an average PSNR above 37 dB and an average SSIM above 0.95. The proposed model provides an effective solution for high-quality CGH applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： computer generated holography

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