检索结果-内蒙古大学图书馆

Combining SEFDM Technique With IBFD Communication System in an ROF Link for Achieving Ultra-High Spectral Efficiency

引用

JOURNAL OF LIGHTWAVE TECHNOLOGY 2025年第3期43卷 1089-1097页

作者： Chen, Yu Chen, Yang East China Normal Univ Sch Commun & Elect Engn Shanghai Key Lab Multidimens Informat Proc Shanghai 200241 Peoples R China

Oriented to the requirements of future high-frequency wireless communication systems, this paper proposes a method of combining spectrally efficient frequency-division multiplexing (SEFDM) technique with the in-band full-duplex (IBFD) communication system and applying it to microwave photonic transmission links to achieve ultra-high spectral efficiency. The microwave photonic link not only realizes the transmission of SEFDM signals received by the IBFD system but also realizes the analog self-interference cancellation (SIC) function. The digital SIC and SEFDM demodulation functions are seamlessly integrated following the analog SIC. Utilizing a cross-iterative algorithm, the adverse effects of the signal of interest (SOI) on the digital SIC of the received signal are mitigated, leading to a substantial improvement in both the SIC depth and demodulation performance of the SEFDM signal compared to the conventional least squares (LS) algorithm. An experiment has been conducted. The SOI and self-interference (SI) have symbol rates of 300 Msym/s and 600 Msym/s, respectively, and share a center frequency of 2 GHz and a bandwidth compression factor of 0.8. When the SI to SOI power ratio is 10.3 dB, the analog SIC depth is around 18.3 dB. The conventional LS algorithm achieves a digital SIC depth of 12.6 dB but the error vector magnitude (EVM) is 13.2%. In contrast, our proposed iterative method improves the SIC depth to 15.1 dB and reduces the EVM to 4.1%. The feasibility of the system is also verified by incorporating a 25.2-km fiber.

关键词： Interference cancellation Demodulation Microwave photonics Optical fibers Microwave theory and techniques Microwave communication Optical fiber dispersion Optical fiber communication Communication systems Signal processing algorithms Digital signal processing in-band full-duplex microwave photonics self-interference cancellation (SIC) spectrally efficient frequency-division multiplexing (SEFDM)

来源：评论

学校读者我要写书评

暂无评论

OmniTracker: Unifying Visual Object Tracking by Tracking-With-Detection

引用

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2025年第4期47卷 3159-3174页

作者： Wang, Junke Wu, Zuxuan Chen, Dongdong Luo, Chong Dai, Xiyang Yuan, Lu Jiang, Yu-Gang Fudan Univ Sch Comp Sci Shanghai Key Lab Intelligent Informat Proc Shanghai Peoples R China Microsoft Res Redmond WA 98052 USA Microsoft Res Asia Beijing 100080 Peoples R China

Visual Object Tracking (VOT) aims to estimate the positions of target objects in a video sequence, which is an important vision task with various real-world applications. Depending on whether the initial states of target objects are specified by provided annotations in the first frame or the categories, VOT could be classified as instance tracking (e.g., SOT and VOS) and category tracking (e.g., MOT, MOTS, and VIS) tasks. Different definitions have led to divergent solutions for these two types of tasks, resulting in redundant training expenses and parameter overhead. In this paper, combing the advantages of the best practices developed in both communities, we propose a novel tracking-with-detection paradigm, where tracking supplements appearance priors for detection and detection provides tracking with candidate bounding boxes for the association. Equipped with such a design, a unified tracking model, OmniTracker, is further presented to resolve all the tracking tasks with a fully shared network architecture, model weights, and inference pipeline, eliminating the need for task-specific architectures and reducing redundancy in model parameters. We conduct extensive experimentation on seven prominent tracking datasets of different tracking tasks, including LaSOT, TrackingNet, DAVIS16-17, MOT17, MOTS20, and YTVIS19, and demonstrate that OmniTracker achieves on-par or even better results than both task-specific and unified tracking models.

关键词： Target tracking Detectors Object tracking Training Feature extraction Trajectory Visualization Pipelines Correlation Benchmark testing Unified tracking models tracking-with-detection single object tracking video object segmentation multiple object tracking multiple object tracking and segmentation video instance segmentation

来源：评论

学校读者我要写书评

暂无评论

Disturbance rejection-based adaptive non-singular fast terminal sliding mode control fora quadrotor under severe turbulent wind

引用

ISA TRANSACTIONS 2025年 157卷 248-257页

作者： Miranda-Moya, Armando Castaneda, Herman Wang, Hesheng Tecnol Monterrey Sch Sci & Engn Av Eugenio Garza Sada 2501 Monterrey 64849 Nuevo Leon Mexico Shanghai Jiao Tong Univ Shanghai Engn Res Ctr Intelligent Control & Manage Key Lab Marine Intelligent Equipment & Syst Key Lab Syst Control Informat ProcMinist EducDep Shanghai 200240 Peoples R China

This paper presents the design of a disturbance rejection-based control strategy fora quadrotor unmanned aerial vehicle subject to model uncertainties and external disturbances described by turbulent wind gusts of severe intensity. First, an extended state observer is introduced to supply full-state and total disturbance estimations within a fixed time regardless of initial estimation errors. Then, an adaptive non-singular fast terminal sliding mode controller with a single-gain structure is proposed to reduce the tuning complexity and drive the pose of the rotorcraft while providing practical finite-time convergence, robustness to bounded external disturbances, non-overestimation of its control gain, and chattering attenuation. Furthermore, the stability of the closed-loop system is guaranteed through homogeneity and Lyapunov theory. Simulation results obtained through the ROS/Gazebo framework demonstrate graphically and quantitatively that the proposed observer-based controller reduces the influence of perturbations and requires less torque effort than existing methods in the presence of sensor noise.

关键词： Adaptive sliding mode control Fixed-time extended state observer Disturbance rejection-based control Robust control Quadrotor UAV

来源：评论

学校读者我要写书评

暂无评论

Semantic Prototyping With CLIP for Few-Shot Object Detection in Remote Sensing Images

引用

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Liu, Tianying Zhou, Shuigeng Li, Wengen Zhang, Yichao Guan, Jihong Tongji Univ Dept Comp Sci & Technol Shanghai 201804 Peoples R China Fudan Univ Shanghai Key Lab Intelligent Informat Proc Shanghai 200438 Peoples R China Fudan Univ Sch Comp Sci Shanghai 200438 Peoples R China

Few-shot object detection (FSOD) has been proposed to solve the problem of insufficient data for training, and it has drawn the attention of the remote sensing community in recent years. A mainstream type of FSOD method is to generate class prototypes based on the limited samples to help the construction of classification decision boundaries. However, these constructed prototypes may be far away from the true class centroids in the few-shot scenario. Recently, the vision-language model (VLM) has shown its powerful ability to align the visual features and text features, which leads to strong zero-shot performance on various downstream computer vision tasks when given only texts. Therefore, in this work, we propose to build class prototypes from text descriptions instead of limited visual instances by leveraging a classical pretrained VLM named CLIP. Concretely, we generate prototypes by feeding the CLIP text encoder with class names and enforcing each positive proposal feature to be close to the corresponding prototype. To accelerate the alignment process, we utilize the CLIP visual encoder as another teacher to achieve visual knowledge distillation. Moreover, we adopt prompt tuning to adapt CLIP to the remote sensing scenario. Extensive experiments on two public FSOD datasets, i.e., DIOR and NWPU VHR-10.v2, demonstrate the effectiveness of our method, which yields competitive results with that of existing approaches.

关键词： Prototypes Object detection Remote sensing Feature extraction Visualization Detectors Training Proposals Transformers Metalearning Few-shot object detection (FSOD) remote sensing images (RSIs) vision-language model (VLM)

来源：评论

学校读者我要写书评

暂无评论

Adversarial Conservative Alternating Q-Learning for Credit Card Debt Collection

引用

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2025年第4期37卷 1542-1555页

作者： Liu, Wenhui Zhu, Jiapeng Ni, Lyu Bi, Jingyu Wu, Zhijian Long, Jiajie Gao, Mengyao Huang, Dingjiang Zhou, Shuigeng East China Normal Univ Sch Data Sci & Engn Shanghai 200062 Peoples R China Bank Shanghai Shanghai 201201 Peoples R China Fudan Univ Sch Comp Sci Shanghai Key Lab Intelligent Informat Proc Shanghai 200438 Peoples R China

Debt collection is utilized for risk control after credit card delinquency. The existing rule-based method tends to be myopic and non-adaptive due to the delayed feedback. Reinforcement learning (RL) has an inherent advantage in dealing with such task and can learn policies end-to-end. However, employing RL here remains difficult because of different interaction processes from standard RL and the notorious problem of optimistic estimations in the offline setting. To tackle these challenges, we first propose an Alternating Q-Learning (AQL) framework to adapt debt collection processes to comparable procedures in RL. Based on AQL, we further develop an Adversarial Conservative Alternating Q-Learning (ACAQL) to address the issue of overoptimistic estimations. Specifically, adversarial conservative value regularization is proposed to balance optimism and conservatism on Q-values of out-of-distribution actions. Furthermore, ACAQL utilizes the counterfactual action stitching to mitigate the overestimation by enhancing behavior data. Finally, we evaluate ACAQL on a real-world dataset created from Bank of shanghai. Offline experimental results show that our approach outperforms state-of-the-art methods and effectively alleviates the optimistic estimation issue. Moreover, we conduct online A/B tests on the bank, and ACAQL achieves at least a 6% improvement of the debt recovery rate, which yields tangible economic benefits.

关键词： Estimation Q-learning Risk management Channel estimation Fraud Electronic mail Decision making Business Standards Credit card debt collection reinforcement learning alternating Q-learning adversarial conservatism counterfactual action stitching counterfactual action stitching

来源：评论

学校读者我要写书评

暂无评论

Fluorescent Metallacycles via Coordination-Driven Self-Assembly: Preparation, Regulation, and Applications

引用

ACCOUNTS OF CHEMICAL RESEARCH 2025年第7期58卷 1151-1167页

作者： Dou, Wei-Tao Yang, Hai-Bo Xu, Lin East China Normal Univ Shanghai Frontiers Sci Ctr Mol Intelligent Synth State Key Lab Petr Mol & Proc Engn Shanghai Key Lab Green Chem & Chem ProcSch Chem & Shanghai 200062 Peoples R China

Fluorescence by small molecular dyes is renowned for its real-time, dynamic, and noninvasive nature. It has become indispensable across scientific domains, including information storage, optoelectronic materials, biosensing, and both diagnosing and treating diseases. Despite their widespread use, these molecular dyes suffer from several limitations due to the sensitivity of their photophysical properties to environmental factors, such as concentration, solvent composition, and polarity. These challenges become particularly prominent when assembling or aggregating fluorescent molecules;their optical characteristics often become unpredictable or uncontrollable. Alternative strategies to stabilize and tune fluorescence during preparation are therefore *** coordination, a classical approach in supramolecular chemistry, offers a promising solution. Coordinating fluorescent dyes to metals precisely directs self-assembly, ensuring defined stoichiometries, geometries, and reversibility. The resulting multifunctional metallacycles combine the advantages inherent to molecular design and fluorescence, pushing the boundaries of fluorescence-based assemblies. We present a modular, directional, and controllable strategy for the self-assembly of supramolecular metallacycles with well-defined geometries, providing a new avenue to address the limitations of traditional small molecular dyes.A key innovation in this research lies in the incorporation of photochromic units into the metallacycles, tuning their photophysical properties reversibly under external illumination. Their emission wavelengths, chiralities, and circularly polarized luminescence (CPL) signals can all be modulated dynamically. These characteristics offer the potential for holographic imaging, where fine control of fluorescence behavior is crucial. We introduce a novel multistep Forster resonance energy transfer (FRET) strategy that enables real-time monitoring of the metallacycle assembly dynamics. Our FR

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Decentralized Framework for Kernel PCA With Projection Consensus Constraints

引用

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2025年第5期47卷 3908-3921页

作者： He, Fan Yang, Ruikai Shi, Lei Huang, Xiaolin Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit MOE Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Fudan Univ Sch Math Sci Shanghai Key Lab Contemporary Appl Math Shanghai 200240 Peoples R China

This paper studies kernel PCA in a decentralized setting, where data are distributively observed with full features in local nodes, and a fusion center is prohibited. Compared with linear PCA, the use of kernel brings challenges to the design of decentralized consensus optimization: the local projection directions are data-dependent. As a result, the consensus constraint in distributed linear PCA is no longer valid. To overcome this problem, we propose a projection consensus constraint and obtain an effective decentralized consensus framework, where local solutions are expected to be the projection of the global solution on the column space of the local dataset. We also derive a fully non-parametric, fast, and convergent algorithm based on the alternative direction method of multiplier, of which each iteration is analytic and communication-efficient. Experiments on a truly parallel architecture are conducted on real-world data, showing that the proposed decentralized algorithm is effective in utilizing information from other nodes and takes great advantages in running time over the central kernel PCA.

关键词： Principal component analysis Kernel Covariance matrices Vectors Optimization Support vector machines Parallel architectures Eigenvalues and eigenfunctions Costs Toy manufacturing industry Kernel methods principal component analysis consensus optimization distributed dataset decentralized algorithms

来源：评论

学校读者我要写书评

暂无评论

Heuristic learning for co-design scheme of optimal sequential attack☆

引用

AUTOMATICA 2025年 174卷

作者： Luo, Xiaoyu Pan, Haoxuan Fang, Chongrong Zhao, Chengcheng Cheng, Peng He, Jianping Shanghai Jiao Tong Univ Dept Automat Key Lab Syst Control & Informat Proc Minist Educ China Shanghai Peoples R China Shanghai Engn Res Ctr Intelligent Control & Manage Shanghai Peoples R China Zhejiang Univ State Key Lab Ind Control Technol Hangzhou Peoples R China

This paper considers a novel co-design problem of the optimal sequential attack, whose attack strategy changes with the time series, and in which the sequential attack selection strategy and sequential attack signal are simultaneously designed. Different from the existing attack design works that separately focus on attack subsets or attack signals, the joint design of the attack strategy poses a huge challenge due to the deep coupling relation between the sequential attack selection strategy and sequential attack signal. In this manuscript, we decompose the sequential co-design problem into two equivalent sub-problems. Specifically, we first derive an analytical closed-form expression between the optimal attack signal and the sequential attack selection strategy. Furthermore, we prove the finite-time inverse convergence of the critical parameters in the injected optimal attack signal by discrete-time Lyapunov analysis, which enables the efficient off-line design of the attack signal and saves computing resources. Finally, we exploit its relationship to design a heuristic two-stage learning-based joint attack algorithm (HTL-JA), which can accelerate the realization of the attack target compared to the one-stage proximal-policy-optimization-based (PPO) algorithm. Extensive simulations are conducted to show the effectiveness of the injected optimal sequential attack. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： False data injection attacks Learning-based methods Attack selection strategy Convergence Co-design scheme

来源：评论

学校读者我要写书评

暂无评论

CMDN: Continuous Human Activity Recognition Based on Multidomain Radar Data Fusion

引用

IEEE SENSORS JOURNAL 2025年第6期25卷 10432-10443页

作者： Feng, Xinxin Chen, Pengcheng Weng, Yuxin Zheng, Haifeng Fuzhou Univ Coll Phys & Informat Engn Fujian Key Lab Intelligent Proc & Wireless Transmi Fuzhou 350108 Peoples R China

Recently, human activity recognition (HAR) has gained significant attention as a research field, leading to the development of diverse technologies driven by its broad range of application scenarios. Radar technology has attracted much attention because of its unique advantages such as not being limited by environmental conditions such as light, shadow, and occlusion. In this article, a continuous HAR system based on multidomain radar data fusion (CMDN) is proposed. Firstly, in order to capture more detailed motion features of the human body, we apply the short-time fractional Fourier transform (STFrFT) to map radar data into the fractional domain, yielding a novel representation of human motion. Secondly, we develop an activity detector based on variable window length short-time average/long-time average (VW-STA/LTA) to accurately identify the start/end points of continuous human actions, addressing the challenge of difficult sequence segmentation in continuous activity recognition tasks. Finally, based on the multi-input multitask (MIMT) recognition network, the features of each domain are processed in parallel, and multiple input representations are fused to obtain the continuous activity classification results with high precision.

关键词： Radar Feature extraction Sensors Radar signal processing Accuracy Radar detection Time-frequency analysis Radar imaging Doppler radar Fractional Fourier transform (FrFT) frequency modulated continuous wave (FMCW) radar human activity recognition (HAR) human activity recognition (HAR)

来源：评论

学校读者我要写书评

暂无评论

Joint Deep Reinforcement Learning and Unfolding for Sensing and Communication Function Selection in Vehicular Networks

引用

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第3期74卷 4933-4945页

作者： Shen, Xiangyu Zheng, Haifeng Lin, Jiayuan Feng, Xinxin Fuzhou Univ Coll Phys & Informat Engn Fujian Key Lab Intelligent Proc & Wireless Transmi Fuzhou 350108 Peoples R China

With the exponential advancement of vehicle networking applications and autonomous driving technology, the demand for efficient and secure autonomous vehicles (AVs) is increasing. AVs require the ability to gather information to navigate complex and ever-changing traffic environments, making effective communication with other vehicles or roadside units (RSUs) crucial for achieving co-awareness. Integrated Sensing and Communication (ISAC) technology emerges as a promising solution for the future of autonomous driving. However, in the dynamic and uncertain real-world road environment, the selection of sensing and communication (SC) functions becomes paramount in enhancing performance. Moreover, ambient noise often disrupts the interaction between vehicles and roadside units, leading to a partial loss of environmental states. To address this challenge, we propose a novel approach for selecting sensing and communication functions, even in the presence of partial loss of environmental states. Specifically, we approximate a partially observable Markov decision process (POMDP) to a complete Markov decision process (MDP) through matrix completion and subsequently utilize deep reinforcement learning (DRL) to solve it. Additionally, we propose a matrix completion algorithm based on the alternating direction method of multipliers (ADMM) with deep unfolding to accurately complete the missing environmental states. Finally, we demonstrate that the proposed method outperforms the other POMDP-based approaches for SC function selection in an ISAC-enabled vehicular network.

关键词： Deep matrix factorization deep unfolding integrated sensing and communication integrated sensing and communication partially observable Markov decision process partially observable Markov decision process vehicular network vehicular network vehicular network

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：