IEEE Access最新文献_第7页

Comprehensive Analysis of Fuel Cell Electric Vehicles: Challenges, Powertrain Configurations, and Energy Management Systems 燃料电池电动汽车综合分析：挑战、动力总成配置和能源管理系统

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3472704

Md Shahin Munsi;Ravi P. Joshi

{"title":"Comprehensive Analysis of Fuel Cell Electric Vehicles: Challenges, Powertrain Configurations, and Energy Management Systems","authors":"Md Shahin Munsi;Ravi P. Joshi","doi":"10.1109/ACCESS.2024.3472704","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472704","url":null,"abstract":"Rising concerns about fuel costs, emissions, oil depletion, and energy security have propelled the search for alternative energy sources in transportation. Electric vehicles are a crucial development in this direction, and fuel cell technology is gaining traction for its versatility and potential benefits. Fuel cells have become increasingly attractive for automobile owing to their ease of use, quiet operation, superior efficiency, modular design, and reliance on clean hydrogen. However, challenges remain, including hydrogen storage, high costs, integration with power electronics, and cold-start capabilities, which continue to impede the widespread adoption of Fuel Cell Electric Vehicles (FCEVs). This study critically examines these key issues, explores various fuel cell technologies and drivetrain architectures, and provides a comparative analysis of different energy storage systems. Furthermore, the study delves into the classification and evaluation of energy management strategies (EMS) for FCEVs. The review ultimately aims to stimulate further research focused on reducing costs, extending fuel cell lifespan, enhancing hydrogen infrastructure, optimizing electronic interfaces, and refining EMS to pave the way for the future of FCEVs.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"145459-145482"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704660","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Collaborative Autonomous Navigation of Quadrotors in Unknown Outdoor Environments: An Active Visual SLAM Approach 未知室外环境中四旋翼飞行器的协作自主导航：主动视觉 SLAM 方法

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3473792

Samaneh Elahian;M. A. Amiri Atashgah;Bahram Tarvirdizadeh

{"title":"Collaborative Autonomous Navigation of Quadrotors in Unknown Outdoor Environments: An Active Visual SLAM Approach","authors":"Samaneh Elahian;M. A. Amiri Atashgah;Bahram Tarvirdizadeh","doi":"10.1109/ACCESS.2024.3473792","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3473792","url":null,"abstract":"The development of an integrated path-planning and Simultaneous Localization and Mapping (ASLAM) system, specifically designed for the autonomous and real-time guidance of quadrotors navigating through unexplored outdoor environments helps to map the generation of unknown natural resources. To achieve this goal, a path-planning methodology that leverages system observability is exploited for a quadrotor. This path-planning method is underpinned by the eigenvalues of the Gramian matrix, which are used as a measure of system observability degree, to increase the precision of the quadrotor’s estimated position. In SLAM, high accuracy in the quadrotor’s state estimation improves the accuracy of the map landmarks position estimation. To enhance the accuracy and fortify system robustness, implementing a centralized distributed architecture within a group of three quadrotors is advocated. In this setup, the role of a central hub for information fusion from all agents and determining the most observable path for the entire group is assigned to the leader quadrotor. An assessment of the proposed path-planning method against a random path-planning approach within a single-agent architecture is conducted across various scenarios. This evaluation compares the Root Mean Square Error (RMSE) of the quadrotor’s state estimation. The results illustrate a notable improvement in accuracy. Furthermore, a comparison is conducted to assess the performance of the multi-agent architecture in contrast to the single-agent architecture using the proposed method. The simulation and experimental results confirm a better accuracy in all scenarios and highlight the increased robustness of the cooperative architecture, particularly in fault scenarios, compared to a single-agent architecture.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"147115-147128"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704676","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resistive Measurement Method for MQ Sensors Based on ADCs of Microcontrollers 基于微控制器 ADC 的 MQ 传感器电阻测量方法

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3472697

Sanya Kaunkid;Apinan Aurasopon;Wanchai Khamsen;Chiraphon Takeang;Nawarat Piladaeng;Jaime Lloret

{"title":"Resistive Measurement Method for MQ Sensors Based on ADCs of Microcontrollers","authors":"Sanya Kaunkid;Apinan Aurasopon;Wanchai Khamsen;Chiraphon Takeang;Nawarat Piladaeng;Jaime Lloret","doi":"10.1109/ACCESS.2024.3472697","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472697","url":null,"abstract":"This paper proposes a system for measuring unknown resistances for metal oxide MQ gas sensors. The circuit configuration is based on the Anderson current loop interface, which connects directly to an Arduino Mega 2560. We analyze errors arising from variations in supply voltage of conventional divider circuits, including those introduced by the Analog-to-Digital Conversion (ADC) of microcontroller. To enhance the accuracy of resistance measurements, a voting technique for selecting the optimal unknown resistances is introduced. In this technique, the digital voltage at each node is analyzed to determine the frequency of occurrence of each level. If a particular voltage level has a frequency of occurrence greater than the reference threshold k, it is selected. If no voltage level meets this criterion, the average of the observed voltage levels is used. From the experimental results, unknown resistances were measured in the range of 362 – 15,\u0000<inline-formula> <tex-math>$397~Omega $ </tex-math></inline-formula>\u0000 with a maximum approximated error of 0.55% with \u0000<inline-formula> <tex-math>$k =90$ </tex-math></inline-formula>\u0000%, while the gas content was measured with a maximum error of approximately 0.24% under conditions of power supply voltage fluctuation from 4.9 to 5.1 V.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"144364-144376"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704671","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142409045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hash-Based Method for Generating Building Information Models From 2D CAD Drawings 从二维 CAD 图纸生成建筑信息模型的哈希方法

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3472610

Kyungjin Kang;Ilkyeun Ra;Sangoh Park

{"title":"Hash-Based Method for Generating Building Information Models From 2D CAD Drawings","authors":"Kyungjin Kang;Ilkyeun Ra;Sangoh Park","doi":"10.1109/ACCESS.2024.3472610","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472610","url":null,"abstract":"A building information model (BIM) encompasses the essential information required for a building’s entire lifecycle, based on a 3D model. However, because building design begins with spatial planning, the initial design is based on a 2D plane. Furthermore, introducing BIM to general buildings is not effective in terms of modeling because of the design cost and the inherent 2D structure of older buildings. Consequently, research conducted over the past few years aimed to automatically generate 3D models from 2D drawings; however, the performance is limited in terms of data structure and methodology. Therefore, this study proposes a method that generates 3D information necessary for generating BIM models from 2D drawings using 2D hash-based data structures and planar graph analysis to resolve the above problem. Time and spatial complexities for planar graph generation from drawings consisting of n line segments among the proposed methods are \u0000<inline-formula> <tex-math>$O(kn)$ </tex-math></inline-formula>\u0000 and \u0000<inline-formula> <tex-math>$O(n)$ </tex-math></inline-formula>\u0000, respectively, where n is the number of the lines in drawing, k satisfies \u0000<inline-formula> <tex-math>$E(p)leq k leq n$ </tex-math></inline-formula>\u0000, and \u0000<inline-formula> <tex-math>$E(p)$ </tex-math></inline-formula>\u0000 denotes the average number of intersections in each hash cell. By applying it to 2D drawing data used in actual architectures, a 3D model could be developed with approximately 2.9% effort compared to the entire 2D drawing being modeled by a worker. This enables designers unfamiliar with BIM environments to conveniently obtain IFC files containing BIM models and then utilize BIM software to harness 3D information.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"147065-147072"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704629","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","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 Comparative Analysis of Machine Learning Techniques for Predicting the Wear Rate of Ceramic Coated Steel 预测陶瓷涂层钢磨损率的机器学习技术比较分析

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3473028

N. Radhika;M. Sabarinathan;S. Sivaraman

{"title":"A Comparative Analysis of Machine Learning Techniques for Predicting the Wear Rate of Ceramic Coated Steel","authors":"N. Radhika;M. Sabarinathan;S. Sivaraman","doi":"10.1109/ACCESS.2024.3473028","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3473028","url":null,"abstract":"Ceramic coatings are necessary for steel as they offer resistance to corrosion, high-temperature degradation, and abrasion, thereby enhancing the wear characteristics of steel structures. Evaluating the wear rate of Ceramic-Coated (CC) steels is crucial for enhancing the reliability and longevity of steel components. Various factors such as microstructural features and operating conditions complicate the wear analysis of CC steel. To overcome this obstacle, the present study employs several Machine Learning (ML) models such as Elastic Net Regressor (ENR), Robust Regressor (RR), Extreme Gradient Boosting Regressors (XGBoost), and Bagging Regressor (BR), to predict the wear rate of CC steel. Pearson Correlation Coefficient (PCC) revealed that the hardness of the coating greatly affects the wear rate. Among various ML regressor models, the BR model exhibited the optimum performance with the R2 of 0.93 with ENR, RR, and XGBoost exhibiting lower R2 values of 0.79, 0.84, and 0.89 respectively. Eventually, the BR model is used to predict the wear rate of TiN and Al2O3-coated steel, and the experimental results of the same are compared. The comparison of results revealed an error percentage of ± 7.78% between the experimental and predicted wear rate.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"146949-146967"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704673","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Winding Function Model of Stand-Alone Synchronous Turbo-Generator With Damper Winding 带阻尼器绕组的独立同步涡轮发电机绕组功能模型

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3473613

Gojko Joksimović;Hamid Ali Khan;Aldin Kajević

{"title":"Winding Function Model of Stand-Alone Synchronous Turbo-Generator With Damper Winding","authors":"Gojko Joksimović;Hamid Ali Khan;Aldin Kajević","doi":"10.1109/ACCESS.2024.3473613","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3473613","url":null,"abstract":"The original dynamic model of the synchronous round-rotor generator also known as synchronous turbo-generator (STG) in stand-alone mode of operation is developed and presented in the paper. The model is based on Winding Function (WF) theory and as such it is derived in the natural frame of reference. Depending on the presence or absence of a damper winding on the rotor two independent mathematical models are derived. The presented model provides an accurate description of the real spatial distribution of all windings in the machine, including the short-circuited damper cage winding. Currents in all windings of the machine over time, including all bars of the damper winding, are output from the model. Moreover, the time required to run the model on a computer of average performance is measured in minutes, which is unimaginably fast compared to similar models based on the Finite Element Method (FEM). On the other hand, the results obtained with a completely different and independent time stepping FEM based model largely confirm the validity of the results obtained with the proposed model.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"144249-144259"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704667","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PEaF-Production Environment Analyzer Framework: Assisting Continuous Deployment of 5G Workloads Using AI/ML PEaF--生产环境分析框架：利用人工智能/移动语言协助 5G 工作负载的持续部署

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3472498

Karthikeyan Subramaniam;Senthil Kumar;Asutosh Mishra;Ayush Bhandari;Jamsheed Manja Ppallan;Ganesh Chandrasekaran

{"title":"PEaF-Production Environment Analyzer Framework: Assisting Continuous Deployment of 5G Workloads Using AI/ML","authors":"Karthikeyan Subramaniam;Senthil Kumar;Asutosh Mishra;Ayush Bhandari;Jamsheed Manja Ppallan;Ganesh Chandrasekaran","doi":"10.1109/ACCESS.2024.3472498","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472498","url":null,"abstract":"A Production Environment Analyzer Framework (PEaF) is proposed to address the limitations of the Continuous Deployment (CD) process for 5G workflow lifecycle management. By integrating an AI/ML-based PEaF into the CD pipeline, we aim to ensure reliable deployments. PEaF uses AI/ML techniques to analyze the production environment and predict the health status of the hardware components. It collects raw data, applies K-Means clustering to group similar data points, and assigns scores to each cluster. These scores serve as features for training Support Vector Machine (SVM) and Random Forest (RF) classifiers to classify hardware health status. Experimental results show that PEaF achieves high classification accuracies of 97.26% and 96.44% for SVM and RF, respectively, with clustering. By analyzing the production environment and excluding deteriorating hardware from the CD, service failures are reduced by at least 27.04%. Moreover, PEaF decreases the polling frequency of hardware status by 48.7%, enhancing operational efficiency. Overall, PEaF contributes to advancing Continuous Integration/Continuous Deployment (CI/CD) practices in the 5G ecosystem, ensuring the reliability and stability of the production environment before deploying/upgrading services.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"147012-147022"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703063","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generating Topic-Agnostic Conversations With LLMs 用 LLM 生成主题识别对话

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3473692

Harshit Sandilya;Naveen Gehlot;Rajesh Kumar;Mahipal Bukya

{"title":"Generating Topic-Agnostic Conversations With LLMs","authors":"Harshit Sandilya;Naveen Gehlot;Rajesh Kumar;Mahipal Bukya","doi":"10.1109/ACCESS.2024.3473692","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3473692","url":null,"abstract":"Conversational systems are important applications of Artificial Intelligence, encompassing a wide variety of implementations, from rule-based systems to complex systems using Natural Language Processing, Deep Neural Networks, and Transformer Architectures. With the growth of these implementations, the quality of conversational data has become a concern. Many attempts have been made to generate such data, focusing primarily on topical conversations. This article presents a generalized framework moving from generating topical conversation towards topic-agnostic conversational data consisting of three Large Language Model instances. Two of these models interact with each other to generate the conversation, while the third one plays the role of a judge to keep the conversation going. The synthetic data created by the proposed method exhibits higher quality and lower toxicity than four of the existing datasets (AmazonQA, Daily Dialog, Open Subtitles, and HUMOD) in terms of six performance measures, namely Toxicity, Severe Toxicity, Obscene, Threat, Insult, and Identity Attack. Compared to other datasets, the performance analysis of the generated data shows the lowest measures in terms of mean and maximum values. Specifically, the percentages for Toxicity, Obscene, Threat, Insult, and Identity Attack are 0.27%, 0.04%, 0.02%, 0.05%, and 0.02%, respectively, while the corresponding maximum values are 90.13%, 29.65%, 3.42%, 67.16% and 0.69%. The generated dataset also shows the maximum concentration, with 99.74% of the data in the range of 0-10% toxicity with just a few outliers.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"145540-145549"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704625","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142409068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable Artificial Intelligence (XAI) for Methods Working on Point Cloud Data: A Survey 针对点云数据工作方法的可解释人工智能 (XAI)：调查

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3472872

Raju Ningappa Mulawade;Christoph Garth;Alexander Wiebel

{"title":"Explainable Artificial Intelligence (XAI) for Methods Working on Point Cloud Data: A Survey","authors":"Raju Ningappa Mulawade;Christoph Garth;Alexander Wiebel","doi":"10.1109/ACCESS.2024.3472872","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472872","url":null,"abstract":"In this work, we provide an overview of the XAI (Explainable Artificial Intelligence) works related to explaining the methods working on point cloud (PC) data. The recent decade has seen a surge in artificial intelligence (AI) and machine learning (ML) algorithms finding applications in various fields dealing with a wide variety of data types such as image and text data. Point cloud data is one of these datatypes that has seen an upward trend in the use of AI/ML algorithms. However, not all these AI algorithms are “white box” models that can be understood by humans easily. Many of them are hard to interpret or understand and thus, require methods to provide explanations for the decision-making process. These methods that attempt to provide explanations or insights into the working of AI models working on various datatypes are grouped under XAI. Even though the use of datatypes such as point clouds for AI models has seen an upward trajectory, we see a lack of survey works documenting the developments in the corresponding XAI field. This issue is addressed through our contribution. We classify the literature based on different criteria such as XAI mechanism used, AI models, their tasks, type of model learning and the type of point cloud data taken into consideration. This can help readers identify works that address specific tasks and obtain corresponding details easily. We also provide useful insights regarding the surveyed papers that highlight interesting aspects of the surveyed literature.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"146830-146851"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704781","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Windowed Octonion Quadratic Phase Fourier Transform: Sharp Inequalities, Uncertainty Principles, and Examples in Signal Processing 窗口八元二次相傅里叶变换：信号处理中的锐不等式、不确定性原理和示例

IF 3.4 3区计算机科学

IEEE Access Pub Date : 2024-10-03 DOI: 10.1109/ACCESS.2024.3473298

Manish Kumar;Bhawna

引用次数: 0