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A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2220-2235页

作者： Jiufang Chen Kechen Liu Xin Luo Ye Yuan Khaled Sedraoui Yusuf Al-Turki MengChu Zhou IEEE the College of Computer Science and Technology Chongqing University of Posts and Telecommunications the Department of Computer Science Columbia University the College of Computer and Information Science Southwest University the Department of Electrical and Computer Engineering Faculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Center of Research Excellence in Renewable Energy and Power Systems the Department of Electrical and Computer EngineeringFaculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Department of Electrical and Computer Engineering New Jersey Institute of Technology

High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable ***, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational ***, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices.

关键词： Data science generalized momentum high-dimensional and incomplete(HDI)data hyper-parameter adaptation latent factor analysis(LFA) particle swarm optimization(PSO)

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Transaction transmission model for blockchain channels based on non-cooperative games

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Science China(information Sciences) 2023年第1期66卷 97-114页

作者： Peiyun ZHANG Chenxi LI Mengchu ZHOU Wenjun HUANG Abdullah ABUSORRAH Omaimah O.BAMASAG Engineering Research Center of Digital Forensics of Ministry of Education School of Computer and SoftwareNanjing University of Information Science and Technology School of Computer and Information Anhui Normal University Department of Electrical and Computer Engineering New Jersey Institute of Technology Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Faculty of Engineering and K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University Department of Computer Science Faculty of Computing and Information Technology Center of Excellence in Smart Environment Research King Abdulaziz University

In blockchain networks, transactions can be transmitted through channels. The existing transmission methods depend on their routing information. If a node randomly chooses a channel to transmit a transaction, the transmission may be aborted due to insufficient funds(also called balance) or a low transmission rate. To increase the success rate and reduce transmission delay across all transactions, this work proposes a transaction transmission model for blockchain channels based on non-cooperative game *** balance, channel states, and transmission probability are fully considered. This work then presents an optimized channel transaction transmission algorithm. First, channel balances are analyzed and suitable channels are selected if their balance is sufficient. Second, a Nash equilibrium point is found by using an iterative sub-gradient method and its related channels are then used to transmit transactions. The proposed method is compared with two state-of-the-art approaches: Silent Whispers and Speedy Murmurs. Experimental results show that the proposed method improves transmission success rate, reduces transmission delay,and effectively decreases transmission overhead in comparison with its two competitive peers.

关键词： Blockchain channel transaction transmission channel balance channel state channel transmission probability non-cooperative game

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Hedge-Embedded Linguistic Fuzzy Neural Networks for Systems Identification and Control

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第10期5卷 4928-4937页

作者： Rafiei, Hamed Akbarzadeh-T, Mohammad-R Ferdowsi University of Mashhad Department of Electrical Engineering Center of Excellence on Soft Computing and Intelligent Information Processing Mashhad*** Iran Chalmers University of Technology Department of Electrical Engineering Center for Bionics and Pain Research Mölndal Gothenburg412 96 Sweden

In the realm of natural language processing, hedge-embedded structures have contributed considerably by appreciating linguistic variables and distinguishing overlapped classes. This aspect of natural languages considerably affects the building of linguistically interpretable architectures for fuzzy neural networks (FNNs). Here, we propose extending the idea of hedge-embedded linguistic fuzzy neural networks (LiFNNs) to the systems identification and control paradigm. This perspective leads us to the universal approximation property for this mathematical construct using the Stone–Weierstrass theorem and the proof of stability for the resulting nonlinear system identification process using the Lyapunov function. Furthermore, the power activation functions in the membership degrees of the proposed network enable linguistic hedge interpretation and more precise learning. Finally, the proposed LiFNN, optimized using a backpropagation learning algorithm, is evaluated on several problems in function approximation (periodic functions and quadratic Hermite function), system identification (a nonlinear system), and direct adaptive control fields. Results show that memberships are more distinguishable in the proposed LiFNN, leading to ∼50% less error on the average and higher granulation and interpretability. © 2020 IEEE.

关键词： Linguistics

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IRS-enabled NOMA communication systems:A network architecture primer with future trends and challenges

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Digital Communications and Networks 2024年第5期10卷 1503-1528页

作者： Haleema Sadia Ahmad Kamal Hassan Ziaul Haq Abbas Ghulam Abbas Muhammad Waqas Zhu Han Faculty of Electrical Engineering and Telecommunications and Networking(TeleCoN)Research Center Ghulam Ishaq Khan Institute of Engineering and Technology(GIKI)Topi 23640Pakistan Faculty of Computer Science and Engineering GIKITopi 23640Pakistan Department of Computer Engineering College of Information TechnologyUniversity of Bahrain32028Bahrain School of Engineering Edith Cowan UniversityPerth WA6027Australia Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004USA Department of Computer Science and Engineering Kyung Hee UniversitySeoul 446-701South Korea

Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless *** provides improved performance in terms of system throughput,spectral efficiency,fairness,and energy efficiency(EE).However,in conventional NOMA networks,performance degradation still exists because of the stochastic behavior of wireless *** combat this challenge,the concept of Intelligent Reflecting Surface(IRS)has risen to prominence as a low-cost intelligent solution for Beyond 5G(B5G)*** this paper,a modeling primer based on the integration of these two cutting-edge technologies,i.e.,IRS and NOMA,for B5G wireless networks is *** in-depth comparative analysis of IRS-assisted Power Domain(PD)-NOMA networks is provided through 3-fold ***,a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems,and parallels are drawn with conventional network configurations,i.e.,conventional NOMA,Orthogonal Multiple Access(OMA),and IRS-assisted OMA *** by this,a comparative analysis of these network configurations is showcased in terms of significant performance metrics,namely,individual users'achievable rate,sum rate,ergodic rate,EE,and outage ***,for multi-antenna IRS-enabled NOMA networks,we exploit the active Beamforming(BF)technique by employing a greedy algorithm using a state-of-the-art branch-reduceand-bound(BRB)*** optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques,i.e.,minimum-mean-square-error,zero-forcing-BF,and ***,we present an outlook on future envisioned NOMA networks,aided by IRSs,i.e.,with a variety of potential applications for 6G wireless *** work presents a generic performance assessment toolkit for wireless networks,focusing on IRS-assisted NOMA *** comparative analysis provides a solid foundation for the dev

关键词： Intelligent reflecting surface Non-orthogonal multiple access 6G Beamforming Sum rate Energy efficiency

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An Improved Method for Approximating the Infinite-Horizon Value Function of the Discrete-Time Switched LQR Problem

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Journal of Systems Science & Complexity 2024年第1期37卷 22-39页

作者： HOU Tan LI Yuanlong LIN Zongli Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Charles L.Brown Department of Electrical and Computer Engineering University of VirginiaCharlottesvilleVA 22904-4743USA

This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR *** particular,the authors propose a new value iteration method to generate a sequence of monotonically decreasing functions that converges exponentially to the value *** method facilitates us to use coarse approximations resulting from faster but less accurate algorithms for further value iteration,and thus,the proposed approach is capable of achieving a better approximation for a given computation time compared with the existing *** numerical examples are presented in this paper to illustrate the effectiveness of the proposed method.

关键词： Optimal control switched linear systems switched LQR problem.

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A High Resolution Convolutional Neural Network with Squeeze and Excitation Module for Automatic Modulation Classification

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China Communications 2024年第10期21卷 132-147页

作者： Duan Ruifeng Zhao Yuanlin Zhang Haiyan Li Xinze Cheng Peng Li Yonghui School of Information Science and Technology Bejing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing 100083China Department of Computer Science and Information Technology La Trobe UniversityMelbourneVIC 3086Australia School of Electrical and Information Engineering the University of SydneySydneyNSW 2006Australia

Automatic modulation classification(AMC) technology is one of the cutting-edge technologies in cognitive radio communications. AMC based on deep learning has recently attracted much attention due to its superior performances in classification accuracy and robustness. In this paper, we propose a novel, high resolution and multi-scale feature fusion convolutional neural network model with a squeeze-excitation block, referred to as HRSENet,to classify different kinds of modulation *** proposed model establishes a parallel computing mechanism of multi-resolution feature maps through the multi-layer convolution operation, which effectively reduces the information loss caused by downsampling convolution. Moreover, through dense skipconnecting at the same resolution and up-sampling or down-sampling connection at different resolutions, the low resolution representation of the deep feature maps and the high resolution representation of the shallow feature maps are simultaneously extracted and fully integrated, which is benificial to mine signal multilevel features. Finally, the feature squeeze and excitation module embedded in the decoder is used to adjust the response weights between channels, further improving classification accuracy of proposed *** proposed HRSENet significantly outperforms existing methods in terms of classification accuracy on the public dataset “Over the Air” in signal-to-noise(SNR) ranging from-2dB to 20dB. The classification accuracy in the proposed model achieves 85.36% and97.30% at 4dB and 10dB, respectively, with the improvement by 9.71% and 5.82% compared to ***, the model also has a moderate computation complexity compared with several state-of-the-art methods.

关键词： automatic modulation classification deep learning feature squeeze-and-excitation high-resolution multi-scale

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Adaptive Two-stage Unscented Kalman Filter for Dynamic State Estimation of Synchronous Generator Under Cyber Attacks Against Measurements

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Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1408-1418页

作者： Dongchen Hou Yonghui Sun Venkata Dinavahi Yi Wang the School of Electrical and Power Engineering Hohai UniversityNanjing 210098China the Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2V4Canada the School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China the Henan Engineering Research Center of Power Electronics and Energy Systems Zhengzhou 450001China

This paper develops an adaptive two-stage unscented Kalman filter(ATSUKF)to accurately track operation states of the synchronous generator(SG)under cyber *** achieve high fidelity,considering the excitation system of SGs,a detailed 9~(th)-order SG model for dynamic state estimation is ***,for several common cyber attacks against measurements,a two-stage unscented Kalman filter is proposed to estimate the model state and the bias in ***,to solve the deterioration problem of state estimation performance caused by the mismatch between noise statistical characteristics and model assumptions,a multi-dimensional adaptive factor matrix is derived to modify the noise covariance ***,a large number of simulation experiments are carried out on the IEEE 39-bus system,which shows that the proposed filter can accurately track the SG state under different abnormal test conditions.

关键词： Cyber attack dynamic state estimation Kalman filtering synchronous generator(SG) unscented transformation

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Privacy and Security Challenges in Federated Learning for UAV Systems: A Systematic Review

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IEEE Access 2025年 13卷 86599-86615页

作者： Farsi, Ahmed Al Khan, Ajmal Mughal, Muhammad Rizwan Bait-Suwailam, Mohammed M. Sultan Qaboos University Communication and Information Research Center Muscat Oman Sultan Qaboos University Department of Electrical and Computer Engineering Muscat Oman

Unmanned Aerial Vehicles have become indispensable assets across various sectors, leveraging their mobility and data collection capabilities. However, privacy and security concerns have fueled interest in Federated Learning as a potential solution. Federated learning (FL), being decentralized and collaborative, holds promise in addressing the privacy risks inherent in centralized data processing while enhancing model performance. In this review, we explore the privacy and security implications of FL in UAV ecosystems. We highlight FL’s potential to mitigate privacy risks by aggregating model updates locally, minimizing data transmission needs. In addition, we examine security challenges and evaluate protective mechanisms. Through a systematic review of the literature, we identified gaps and proposed future research directions, with the aim of improving the security and privacy of FL in UAV applications. Our findings highlight advanced strategies, such as secure aggregation, adversarial defenses, and lightweight cryptographic techniques, to mitigate privacy and security threats in Federated Learning-based UAV. They also underscore the need for real-world validations and regulatory frameworks to ensure resilient and ethically governed deployments in UAV networks. © 2013 IEEE.

关键词： Drones

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HDCGD-CBAM:Satellite Interference Recognition Algorithm Based on Improved CLDNN and CBAM

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China Communications 2024年第12期21卷 257-274页

作者： Duan Ruifeng Chen Ziyu Meng Wei Wang Xu Yang Guoting Cheng Peng Li Yonghui School of Information Science and Technology Beijing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing 100083China Jining Economic and Social Development Research Center Jining 272000China School of Electrical and Information Engineering the University of SydneySydneyNSW 2006Australia Department of Computer Science and Information Technology La Trobe UniversityMelbourneVIC 3086Australia

Satellite communication systems are facing serious electromagnetic interference,and interference signal recognition is a crucial foundation for targeted *** this paper,we propose a novel interference recognition algorithm called HDCGD-CBAM,which adopts the time-frequency images(TFIs)of signals to effectively extract the temporal and spectral *** the proposed method,we improve the Convolutional Long Short-Term Memory Deep Neural Network(CLDNN)in two ***,the simpler Gate Recurrent Unit(GRU)is used instead of the Long Short-Term Memory(LSTM),reducing model parameters while maintaining the recognition ***,we replace convolutional layers with hybrid dilated convolution(HDC)to expand the receptive field of feature maps,which captures the correlation of time-frequency data on a larger spatial ***,Convolutional Block Attention Module(CBAM)is introduced before and after the HDC layers to strengthen the extraction of critical features and improve the recognition *** experiment results show that the HDCGD-CBAM model significantly outper-forms existing methods in terms of recognition accuracy and *** Jamming-to-Signal Ratio(JSR)varies from-30dB to 10dB,it achieves an average accuracy of 78.7%and outperforms the CLDNN by 7.29%while reducing the Floating Point Operations(FLOPs)by 79.8%to ***,the proposed model has fewer parameters with 301k compared to several state-of-the-art methods.

关键词： attention mechanism CLDNN HDC interference recognition satellite communication

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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