Electronics Letters最新文献_第10页

Characteristic Portrait Construction of Voltage in Substation Areas Using ISSA-Based Cluster Prediction 基于issa聚类预测的变电站区域电压特征画像构建

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-07-02 DOI: 10.1049/ell2.70313

Sicheng Huang, Lijia Ren, Dongbing Tong

{"title":"Characteristic Portrait Construction of Voltage in Substation Areas Using ISSA-Based Cluster Prediction","authors":"Sicheng Huang, Lijia Ren, Dongbing Tong","doi":"10.1049/ell2.70313","DOIUrl":"10.1049/ell2.70313","url":null,"abstract":"To effectively utilize power data for monitoring and issuing warnings in distribution-substation areas, a clustering prediction model was developed by integrating an improved salp swarm optimization algorithm. First, power characteristics related to the target were collected using original data mining and dimensionality reduction techniques. A voltage-characteristic label model for the substation areas was then developed, focusing on three dimensions: safety (S), stability (S), and economy (E). Next, because the improved salp swarm algorithm (ISSA) has better optimization effect and less iteration time, the fusion ISSA was combined with the K-means clustering algorithm to analyse the data, while the ISSA-BP neural network algorithm was used for time-series prediction. This approach generated a voltage profile and detected abnormal conditions in the substation areas. Finally, the model was validated using real data from a substation area in Shanghai. The results demonstrated that the proposed algorithm was more efficient, with improved prediction accuracy and performance metrics.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70313","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Bit-Serial Compute-Transfer Architecture for High-Speed Data Processing in Chip-to-Chip Systems 用于片对片系统中高速数据处理的位串行计算机传输体系结构

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-07-02 DOI: 10.1049/ell2.70352

Xiaoshu Cheng, Siyi Pan, Yiwen Wang, Weiran Ding, Ping Li

引用次数: 0

Deep Feature Retrieval With Human-in-the-Loop for Underwater Hull Fouling Segmentation 基于人在环深度特征检索的水下船体污垢分割

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-07-01 DOI: 10.1049/ell2.70332

Yajuan Gu, Jiawen Zhao, Junjie Zhang

引用次数: 0

Vehicle Target Detection Based on Cross-Modality Projective-Invariant Features Extracted from Unpaired SAR and Infrared Images 基于非配对SAR和红外图像交叉模态投影不变特征的车辆目标检测

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-06-30 DOI: 10.1049/ell2.70336

Zhe Geng, Chongqi Xu, Chen Xin, Xiang Yu, Daiyin Zhu

{"title":"Vehicle Target Detection Based on Cross-Modality Projective-Invariant Features Extracted from Unpaired SAR and Infrared Images","authors":"Zhe Geng, Chongqi Xu, Chen Xin, Xiang Yu, Daiyin Zhu","doi":"10.1049/ell2.70336","DOIUrl":"10.1049/ell2.70336","url":null,"abstract":"Synthetic aperture radar (SAR) automatic target recognition (ATR) is remarkably challenging since the SAR image defies the foundation for human and computer vision, i.e., the Gestalt perceptual principles. We propose to address this problem by fusing the target features reflected in SAR and infrared (IR) images via a novel dual-channel context-guided feature-alignment network (CGFAN) that is capable of fusing the cross-modality projective-invariant features extracted from unpaired SAR and IR images. First, region of interest (ROI) matching between SAR and IR images is realized based on special landmarks exhibiting consistent cross-modality features. After that, generative models trained with historical SAR and IR images are used to synthesize SAR images based on the IR images collected in real time for the current mission. Since SAR imaging takes more time than IR imaging, by using these synthesized SAR images as auxiliary data, the spatial-coverage rate in a typical collaborative SAR/IR ATR mission carried out by drone swarms is effectively improved. The proposed CGFAN is tested against the proprietary monostatic-bistatic circular SAR and IR dataset constructed by the researchers at our institution, which consists of nine types of military vehicles. Experimental results show that the proposed CGFAN offers better ATR performance than the baseline networks.A novel dual-channel CGFAN that is capable of fusing the cross-modality projective-invariant features extracted from unpaired SAR and IR images is proposed. First, ROI matching between SAR and IR images are realized based on special landmarks exhibiting consistent cross-modality features. After that, generative models trained with historical SAR and IR images are used to synthesize SAR images based on the IR images collected in real time for the current mission.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70336","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Energy-Delay Tradeoff in Heterogeneous Distributed Computing Systems 异构分布式计算系统的最优能量延迟权衡

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-06-30 DOI: 10.1049/ell2.70349

Linglin Kong, Chi Wan Sung

{"title":"Optimal Energy-Delay Tradeoff in Heterogeneous Distributed Computing Systems","authors":"Linglin Kong, Chi Wan Sung","doi":"10.1049/ell2.70349","DOIUrl":"10.1049/ell2.70349","url":null,"abstract":"This letter investigates the workload allocation in heterogeneous distributed computing systems. The optimal energy-delay tradeoff is completely characterized by identifying all the Pareto optimal solutions in a bi-objective optimization problem. For the scenario with a large number of subtasks, the problem is approximated by continuous relaxation, which can be solved with the time complexity of <math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>O</mi>\u0000 <mo>(</mo>\u0000 <msup>\u0000 <mi>N</mi>\u0000 <mn>2</mn>\u0000 </msup>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 <annotation>$mathcal {O}(N^2)$</annotation>\u0000 </semantics></math>, where <math>\u0000 <semantics>\u0000 <mi>N</mi>\u0000 <annotation>$N$</annotation>\u0000 </semantics></math> is the number of computing devices. Numerical studies show the effectiveness of our approaches and demonstrate the energy-delay tradeoff in distributed computing systems.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70349","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fine-Grained Temporal Encoding and Decoding-Based Underwater Object Tracking 基于细粒度时间编码和解码的水下目标跟踪

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-06-28 DOI: 10.1049/ell2.70346

Zhen Sun, Zhenggang Guan, Qinghua Li, Mengyang Yuan, Haonan Sun

{"title":"Fine-Grained Temporal Encoding and Decoding-Based Underwater Object Tracking","authors":"Zhen Sun, Zhenggang Guan, Qinghua Li, Mengyang Yuan, Haonan Sun","doi":"10.1049/ell2.70346","DOIUrl":"10.1049/ell2.70346","url":null,"abstract":"Underwater object tracking is a highly challenging task in the field of computer vision. This study focuses on this domain and proposes an innovative fine-grained temporal encoding and decoding-based underwater object tracking method. Due to the complex and dynamic underwater environment, such as uneven lighting, turbid water quality, and complex target motion patterns, existing underwater object tracking methods face significant limitations in accuracy and stability. By carefully designing a refinement module that combines fine-grained consistency and candidate elimination, this method can accurately extract fine-grained features of the target and effectively mitigate the interference of various underwater complexities during feature extraction, thereby improving the precision of target features. Furthermore, leveraging the temporal encoding–decoding module, the target features are continuously propagated along the temporal sequence, allowing full utilization of the relational information between frames, which further enhances tracking stability. Experiments were conducted on the UVOT400 dataset, which is large-scale and rich in attributes with diverse target categories. The results demonstrate that, compared to existing methods, this approach significantly outperforms in both accuracy and stability of underwater object tracking, providing new insights and effective solutions for the advancement of underwater object tracking technology.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70346","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144503288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Low Power, High Input Dynamic Range and High Precision Current-Mode Loser-Take-All Circuit 一种低功耗、高输入动态范围、高精度电流模式输者通吃电路

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-06-26 DOI: 10.1049/ell2.70347

Bashir Makki Jebur, Doaa Hameed Majeed, Hossein Yaghoobzadeh Shadmehri, Ehsan Rahiminejad

引用次数: 0

Metaheuristic Algorithm-Based Antenna Selection Collaborative Beamforming for Remote Sensors 基于元启发式算法的遥感器天线选择协同波束形成

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-06-26 DOI: 10.1049/ell2.70343

Semyoung Oh, Daejin Park

引用次数: 0

A Training Sample Selection Method With Fusing GIP Statistic and Geographic Information for Airborne Radar 基于gis统计和地理信息融合的机载雷达训练样本选择方法

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-06-25 DOI: 10.1049/ell2.70345

Chenran Gao, Wenchong Xie, Yuanyi Xiong, Wei Chen, Buqiu Tian

引用次数: 0

Multi-Agent Reinforcement Learning With Deep Networks for Diverse Q $Q$ -Vectors 多元Q$ Q$ -向量的深度网络多智能体强化学习

IF 0.8 4区工程技术

Electronics Letters Pub Date : 2025-06-24 DOI: 10.1049/ell2.70342

Zhenglong Luo, Zhiyong Chen, Shijian Liu, James Welsh

{"title":"Multi-Agent Reinforcement Learning With Deep Networks for Diverse \u0000 \u0000 Q\u0000 $Q$\u0000 -Vectors","authors":"Zhenglong Luo, Zhiyong Chen, Shijian Liu, James Welsh","doi":"10.1049/ell2.70342","DOIUrl":"10.1049/ell2.70342","url":null,"abstract":"In multi-agent reinforcement learning (MARL) tasks, the state-action value, commonly referred to as the <math>\u0000 <semantics>\u0000 <mi>Q</mi>\u0000 <annotation>$Q$</annotation>\u0000 </semantics></math>-value, can vary among agents because of their individual rewards, resulting in a <math>\u0000 <semantics>\u0000 <mi>Q</mi>\u0000 <annotation>$Q$</annotation>\u0000 </semantics></math>-vector. Determining an optimal policy is challenging, as it involves more than just maximizing a single <math>\u0000 <semantics>\u0000 <mi>Q</mi>\u0000 <annotation>$Q$</annotation>\u0000 </semantics></math>-value. Various optimal policies, such as a Nash equilibrium, have been studied in this context. Algorithms like Nash Q-learning and Nash Actor-Critic have shown effectiveness in these scenarios. This paper extends this research by proposing a deep Q-networks algorithm capable of learning various <math>\u0000 <semantics>\u0000 <mi>Q</mi>\u0000 <annotation>$Q$</annotation>\u0000 </semantics></math>-vectors using Max, Nash, and Maximin strategies. We validate the effectiveness of our approach in a dual-arm robotic environment, a representative human cyber-physical systems (HCPS) scenario, where two robotic arms collaborate to lift a pot or hand over a hammer to each other. This setting highlights how incorporating MARL into HCPS can address real-world complexities such as physical constraints, communication overhead, and dynamic interactions among multiple agents.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70342","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0