检索结果-内蒙古大学图书馆

Wireless Federated Learning Over Resource-Constrained Networks: Digital Versus Analog Transmissions

IEEE Transactions on Wireless Communications 2024年第10期23卷 14020-14036页

作者： Yao, Jiacheng Xu, Wei Yang, Zhaohui You, Xiaohu Bennis, Mehdi Poor, H. Vincent Southeast University Nanjing210096 China Zhejiang Laboratory Hangzhou311121 China The College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China The Center for Wireless Communications Oulu University Oulu90014 Finland The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

To enable wireless federated learning (FL) in communication resource-constrained networks, two communication schemes, i.e., digital and analog ones, are effective solutions. In this paper, we quantitatively compare these two techniques, highlighting their essential differences as well as respectively suitable scenarios. We first examine both digital and analog transmission schemes, together with a unified and fair comparison framework under imbalanced device sampling, strict latency targets, and transmit power constraints. A universal convergence analysis under various imperfections is established for evaluating the performance of FL over wireless networks. These analytical results reveal that the fundamental difference between the digital and analog communications lies in whether communication and computation are jointly designed or not. The digital scheme decouples the communication design from FL computing tasks, making it difficult to support uplink transmission from massive devices with limited bandwidth and hence the performance is mainly communication-limited. In contrast, the analog communication allows over-the-air computation (AirComp) and achieves better spectrum utilization. However, the computation-oriented analog transmission reduces power efficiency, and its performance is sensitive to computation errors from imperfect channel state information (CSI). Furthermore, device sampling for both schemes are optimized and differences in sampling optimization are analyzed. Numerical results verify the theoretical analysis and affirm the superior performance of the sampling optimization. © 2002-2012 IEEE.

关键词： Channel state information

来源：评论

学校读者我要写书评

暂无评论

An Empirical Study of Super-Resolution on Low-Resolution Micro-Expression Recognition

引用

IEEE Transactions on Affective Computing 2025年

作者： Zhou, Ling Wang, Mingpei Huang, Xiaohua Zheng, Wenming Mao, Qirong Zhao, Guoying Macau University of Science and Technology School of Computer Science and Engineering 999078 China Nanjing Institute of Technology School of International Education Oulu School Jiangsu Nanjing211167 China Southeast University Key Laboratory of Child Development and Learning Science Ministry of Education Nanjing210096 China Southeast University Research Center for Learning Science China Southeast University School of Biological Science and Medical Engineering Jiangsu Nanjing210096 China Jiangsu University School of Computer Science and Communication Engineering Jiangsu Zhenjiang212013 China University of Oulu Center for Machine Vision and Signal Analysis 90014 Finland

Micro-expression recognition (MER) in low-resolution (LR) scenarios presents an important and complex challenge, particularly for practical applications such as group MER in crowded environments. Despite considerable advancements in super-resolution (SR) techniques for enhancing the quality of LR images and videos, few study has focused on investigate SR for improving LR MER. The scarcity of investigation can be attributed to the inherent difficulty in capturing the subtle motions of micro-expressions, even in original-resolution MER samples, which becomes even more challenging in LR samples due to the loss of distinctive features. Furthermore, a lack of systematic benchmarking and thorough analysis of SR-assisted MER methods has been noted. This paper tackles these issues by conducting a series of benchmark experiments that integrate both SR and MER methods, guided by an in-depth literature survey. Specifically, we employ seven cutting-edge state-of-the-art (SOTA) MER techniques and evaluate their performance on samples generated from 22 SOTA SR techniques, thereby addressing the problem of SR in MER. Through our empirical study, we uncover the primary challenges associated with SR-assisted MER and identify avenues to tackle these challenges by leveraging recent advancements in both SR and MER methodologies. Our analysis provides insights for progressing toward more efficient SR-assisted MER. © 2010-2012 IEEE.

关键词： Optical resolving power

来源：评论

学校读者我要写书评

暂无评论

FedMLC: White-box Model Watermarking for Copyright Protection in Federated Learning for IoT Environment

引用

IEEE Internet of Things Journal 2025年

作者： Chen, Weitong Zhang, Wei Wu, Di Keskinarkaus, Anja Seppanen, Tapio Zhang, Jiale Gao, Longxiang Luan, Tom H. Yangzhou University School of Information Engineering Yangzhou225009 China ToowoombaQLD4350 Australia University of Oulu Physiological Signal Analysis Team Center for Machine Vision and Signal Analysis Oulu90014 Finland University of Southern Queensland SoMPC ToowoombaQLD4350 Australia Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China Xi'an Jiaotong University School of Cyber Science and Engineering Xi'an710049 China

With the widespread application of the Internet of Things (IoT), data processing has gradually migrated to edge devices that are closer to the data source. This shift has significantly improved the ability of real-time data analysis while effectively reducing bandwidth requirements and latency. Furthermore, Federated Learning (FL) has been introduced as a decentralized training method to achieve collaborative training of multiple devices while ensuring local data privacy. However, malicious clients in FL may theft trained models for unauthorized use, which causes model misuse or copyright challenges. To address these issues, this paper proposes FedMLC (Malicious client detection, Leakage tracing, and Copyright verification), a server-side white-box watermarking scheme. FedMLC utilizes the embedded watermark at different stages to achieve both traceability and copyright verification, simplifying the watermarking process. Additionally, the watermarking can also detect malicious clients in FL. Specifically, FedMLC uses the regularization term to guide the parameter signs of the normalization layer to be consistent with the watermark sign, thereby achieving watermark embedding. Experimental results show that our FL model watermarking scheme excels in malicious client detection, leakage tracing, and copyright verification, with minimal impact on model performance, able to resist various attacks such as fine-tuning, pruning, and quantization. © 2014 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Searching for an Accurate Robot Calibration via Improved Levenberg–Marquardt and Radial Basis Function System

引用

Journal of Field Robotics 2025年第0期

作者： Li, Zhibin Deng, Xun Chen, Tinghui Yang, Yuhang Chen, Linlin Yang, Xiwen Hu, Zhenzhen Hu, Lun Hu, Pengwei Li, Shuai Luo, Xin Xinjiang Technical Institute of Physics & Chemistry Chinese Academy of Sciences Urumqi China School of Software Engineering Chengdu University of Information Technology Chengdu China Dazhou Key Laboratory of Government Data Security Sichuan University of Arts and Science Dazhou China School of Software Engineering Xinjiang University Urumqi China Faculty of Information Technology and Electrical Engineering University of Oulu Oulu Finland VTT-Technical Research Centre of Finland Oulu Finland College of Computer and Information Science Southwest University Chongqing China

Robots are frequently utilized in manufacturing, aviation, and other industries, which enhance industrial production efficiency and quality. Specifically, robots perform high-precision tasks like welding, assembly and material handling, which reduce the intensity of manual labor in factories. In the logistics field, robots automatically sort and deliver goods, thereby speeding up supply chain operations. However, the prolonged operation of robots suffers from a decline in positioning accuracy, which makes them unable to satisfy task requirements. To address this challenging issue, this study designs an efficient calibration system integrating the Levenberg–Marquardt algorithm with fuzzy proportion integration differentiation controller and radial basis function neural network. The innovations of this method include: (1) integrating the fuzzy proportion integration differentiation controller into the updating rules of Levenberg–Marquardt algorithm, which further enhances the identification performance of kinematic errors;(2) adopting the radial basis function neural network to handle the robot dynamic errors, which addresses the complexity of dynamic error sources. Extensively experimental robot positioning points are gathered on an HSR JR680 robot, and then experimental validations are conducted by using the designed calibration system. The experiments indicate that the developed algorithm outperforms these existing advanced algorithms. © 2025 Wiley Periodicals LLC.

关键词： Radial basis function networks

来源：评论

学校读者我要写书评

暂无评论

VisioPhysioENet: Multimodal Engagement Detection using Visual and Physiological Signals

arXiv

引用

arXiv 2024年

作者： Singh, Alakhsimar Verma, Nischay Goyal, Kanav Singh, Amritpal Kumar, Puneet Li, Xiaobai Computer Science and Engineering Department National Institute of Technology Jalandhar India Center for Machine Vision and Signal Analysis University of Oulu Finland The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China

This paper presents VisioPhysioENet, a novel multimodal system that leverages visual and physiological signals to detect learner engagement. It employs a two-level approach for extracting both visual and physiological features. For visual feature extraction, Dlib is used to detect facial landmarks, while OpenCV provides additional estimations. The face_recognition library, built on Dlib, is used to identify the facial region of interest specifically for physiological signal extraction. Physiological signals are then extracted using the plane-orthogonal-to-skin method to assess cardiovascular activity. These features are integrated using advanced machine learning classifiers, enhancing the detection of various levels of engagement. We thoroughly tested VisioPhysioENet on the DAiSEE dataset. It achieved an accuracy of 63.09%. This shows it can better identify different levels of engagement compared to many existing methods. It performed 8.6% better than the only other model that uses both physiological and visual features. Copyright © 2024, The Authors. All rights reserved.

关键词： Physiological models

来源：评论

学校读者我要写书评

暂无评论

An Empirical Study of Super-resolution on Low-resolution Micro-expression Recognition

arXiv

引用

arXiv 2023年

作者： Zhou, Ling Wang, Mingpei Huang, Xiaohua Zheng, Wenming Mao, Qirong Zhao, Guoying The School of Computer Science and Engineering Macau University of Science and Technology China The Key Laboratory of Child Development and Learning Science Ministry of Education Southeast University Nanjing210096 China School of Computer Engineering Nanjing Institute of Technology Jiangsu China The School of Biological Science and Medical Engineering Southeast University Jiangsu Nanjing210096 China The School of Computer Science and Communication Engineering Jiangsu University Jiangsu Zhenjiang China The Center for Machine Vision and Signal Analysis University of Oulu Finland

Micro-expression recognition (MER) in low-resolution (LR) scenarios presents an important and complex challenge, particularly for practical applications such as group MER in crowded environments. Despite considerable advancements in super-resolution techniques for enhancing the quality of LR images and videos, few study has focused on investigate super-resolution for improving LR MER. The scarcity of investigation can be attributed to the inherent difficulty in capturing the subtle motions of micro-expressions, even in original-resolution MER samples, which becomes even more challenging in LR samples due to the loss of distinctive features. Furthermore, a lack of systematic benchmarking and thorough analysis of super-resolution-assisted MER methods has been noted. This paper tackles these issues by conducting a series of benchmark experiments that integrate both super-resolution (SR) and MER methods, guided by an in-depth literature survey. Specifically, we employ seven cutting-edge state-of-the-art (SOTA) MER techniques and evaluate their performance on samples generated from 13 SOTA SR techniques, thereby addressing the problem of super-resolution in MER. Through our empirical study, we uncover the primary challenges associated with SR-assisted MER and identify avenues to tackle these challenges by leveraging recent advancements in both SR and MER methodologies. Our analysis provides insights for progressing toward more efficient SR-assisted MER. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Digital versus Analog Transmissions for Federated Learning over Wireless Networks

Digital versus Analog Transmissions for Federated Learning o...

引用

IEEE International Conference on Communications (ICC)

作者： Jiacheng Yao Wei Xu Zhaohui Yang Xiaohu You Mehdi Bennis H. Vincent Poor National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Center for Wireless Communications University of Oulu Oulu Finland Department of Elect. & Computer Eng. Princeton University Princeton NJ USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

In this paper, we quantitatively compare these two effective communication schemes, i.e., digital and analog ones, for wireless federated learning (FL) over resource-constrained networks, highlighting their essential differences as well as their respective application scenarios. We first examine both digital and analog transmission methods, together with a unified and fair comparison scheme under practical constraints. A universal convergence analysis under various imperfections is established for FL performance evaluation in wireless networks. These analytical results reveal that the fundamental difference between the two paradigms lies in whether communication and computation are jointly designed or not. The digital schemes decouple the communication design from specific FL tasks, making it difficult to support simultaneous uplink transmission of massive devices with limited bandwidth. In contrast, the analog communication allows over-the-air computation (AirComp), thus achieving efficient spectrum utilization. However, computation-oriented analog transmission reduces power efficiency, and its performance is sensitive to computational errors. Finally, numerical simulations are conducted to verify these theoretical observations.

关键词： Performance evaluation Wireless sensor networks Accuracy Uncertainty Federated learning Wireless networks Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Cooperative Jamming and Relay Selection for Covert Communications

arXiv

引用

arXiv 2023年

作者： Gao, Chan Yang, Bin Zheng, Dong Jiang, Xiaohong Taleb, Tarik National Engineering Laboratory for Wireless Security School of Cybersecurity Xi’an University of Posts and Telecommunications Xi’an710121 China School of Computer and Information Engineering Chuzhou University China School of Systems Information Science Future University Hakodate Japan Information Technology and Electrical Engineering University of Oulu Oulu90570 Finland Department of Computer and Information Security Sejong University Seoul05006 Korea Republic of

This paper investigates the covert communications via cooperative jamming and relay selection in a wireless relay system, where a source intends to transmit a message to its destination with the help of a selected relay, and a warden attempts to detect the existence of wireless transmissions from both the source and relay, while friendly jammers send jamming signals to prevent warden from detecting the transmission process. To this end, we first propose two relay selection schemes, namely random relay selection (RRS) and max-min relay selection (MMRS), as well as their corresponding cooperative jamming (CJ) schemes for ensuring covertness in the system. We then provide theoretical modeling for the covert rate performance under each relay selection scheme and its CJ scheme and further explore the optimal transmit power controls of both the source and relay for covert rate maximization. Finally, extensive simulation/numerical results are presented to validate our theoretical models and also to illustrate the covert rate performance of the relay system under cooperative jamming and relay selection. Copyright © 2023, The Authors. All rights reserved.

关键词： Jamming

来源：评论

学校读者我要写书评

暂无评论

Digital versus Analog Transmissions for Federated Learning over Wireless Networks

arXiv

引用

arXiv 2024年

作者： Yao, Jiacheng Xu, Wei Yang, Zhaohui You, Xiaohu Bennis, Mehdi Poor, H. Vincent National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Center for Wireless Communications University of Oulu Oulu Finland Department of Elect. & Computer Eng. Princeton University PrincetonNJ United States

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Semantic-Aware Remote State Estimation in Digital Twin with Minimizing Age of Incorrect Information

Semantic-Aware Remote State Estimation in Digital Twin with ...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Haonan Tong Sihua Wang Zhaohui Yang Jun Zhao Mehdi Bennis Changchuan Yin Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China College of Information Science and Electronic-Engineering Zhejiang University Hangzhou China School of Computer Science and Engineering Nanyang Technological University Singapore Centre for Wireless Communications University of Qulu Oulu Finland

In this paper, we investigate the semantic-aware efficient sampling policy for remote state estimation in a digital twin (DT) empowered smart factory with multiple wireless sensing devices and an edge server. In this setting, wireless sensing devices must continuously sample the factory states and transmit semantic-aware sensing data to the server. Using the received sensing data, the server builds a realtime DT mapping remotely that analyzes and predicts the events in the factory. Since the DT requires continuous data transmission, maintaining the DT inevitably consumes significant amounts of limited wireless resources. To address this issue, we reduce the required amount of data transmission by making wireless devices only send the semantic-aware sensing data that indicates the occurrence of events, otherwise stay idle. In particular, we first invoke the age of incorrect information (AoII) to measure the semantic of the sensing data, which represents the freshness of the concerned events. Next, we formulate an optimization problem that minimizes the long-term AoII of remote state estimation through the devices deciding whether to sample the factory states at each time slot. To solve this problem, we first transform the original problem into a state-wise constrained Markov decision programming (CMDP) and then propose a soft actor-critic (SAC) based algorithm to learn a sampling policy to take sample actions within the sampling rate constraint, while considering packet error. Simulation results show that, the proposed algorithm can reduce the number of samples by up to 44% compared to the error-based sampling scheme, with the same estimation accuracy.

关键词：

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：