检索结果-内蒙古大学图书馆

IEEE Transactions on Green Communications and Networking 2024年

作者： Sun, Wei Li, Jingsi Guo, Pengxing He, Xiangyu Wang, Zimo Hu, Cong Liu, Weichen Hou, Weigang Guo, Lei School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Institute of Intelligent Communications and Network Security Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and Telecommunications Chongqing400065 China Guangxi Key Laboratory of Automatic Detecting Technology and Instruments Guilin University of Electronic Technology Guilin541004 China School of Computer Science and Engineering Nanyang Technological University Singapore

Optical networks-on-chips (ONoCs) have emerged as the most promising solution for on-chip interconnection networks, offering distinct advantages such as high bandwidth and low latency. However, traditional wired-based ONoCs often suffer from a high average number of hops, leading to challenges such as increased insertion loss, crosstalk noise, and energy consumption. Therefore, this paper presents a novel ONoC structure known as the metasurface ONoC (MSONoC), which integrates wired waveguide and free-space optical (FSO) transmission with the assistance of metasurfaces. Specifically, this work encompasses the design of a passive metasurface structure tailored for ONoCs, a virtual network cluster partitioning method, an optical metasurface access points select strategy, and a shortest-path routing algorithm. Performance verification is conducted using a modified Noxim simulator. The simulation results demonstrate that the proposed MSONoC offers advantages over traditional NoCs, radio frequency (RF)-based hybrid wired/wireless NoCs, and wired-based ONoCs in terms of throughput, delay, energy consumption, and signal-to-noise ratio under both synthetic traffic and real traffic models. These improvements proves the effectiveness of the MSONoC architecture in optimizing network performance, making it a promising solution for high-performance, energy-efficient communication in on-chip networks. © 2017 IEEE.

关键词： Network-on-chip

来源：评论

学校读者我要写书评

暂无评论

Comparative analysis of the MPPT methods employed in the PV system, involving incremental conductance control and sliding mode control

Comparative analysis of the MPPT methods employed in the PV ...

引用

Energy Transition and Security (ICETS), International Conference on

作者： Fadila Tahiri Abdelkader Harrouz Gazi Erkan Bostanci Mohamed Amine Hartani Abdessalam Badoud Seddik Zemitte Ibrahim Yaichi Elabbes Maatallah Laboratoire de Dévelpment Durable et D’Informatique(LDDI) University of Ahmed Draia Adrar Adrar Algeria Computer Engineering Department Ankara University Turkey Automatic Laboratory University of Ferhat Abbas Setif 1 Setif Algeria

The objective of this research paper is to investigate diverse strategies for achieving optimal maximum power point tracking (MPPT) in photovoltaic (PV) systems. The research delves into the evaluation and comparison of two distinct MPPT techniques: incremental conductance (InC) and sliding mode control (SMC). A DC/DC boost converter is employed between the PV system and the load to facilitate the efficient transfer of the maximum available power. Conventional MPPT methods, such as InC, have shown limitations in detecting and accurately tracking the high point, resulting in a notable power loss. To address this issue, a proposed solution is the utilization of sliding mode control. This method has a number of benefits, including as accurate reference tracking, low distortion in current output, and resilience to changes in parameters. However, a challenge with this technique is the occurrence of pronounced oscillations during transitional periods. The results of simulation confirm that the outcomes achieved through The MPPT SMC outperforms the MPPT INC in relation to tracking the MPP, leading to reduced power losses. This suggests an improvement in the overall efficiency of the system. Additionally, the voltage and current are higher than in MPPT with InC. However, oscillations are more noticeable when using MPPT with SMC.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Quality Assessment of Electrocardiogram Signals Using Contrastive Learning

Quality Assessment of Electrocardiogram Signals Using Contra...

引用

IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Meiping Zhong Zuoyong Li ChuanSheng Wang Jiayan Huang WanQi Zhao Haoyi Fan College of Computer and Big Data Fuzhou University Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China Department of Automatic Control Technical Polytechnic University of Catalonia Barcelona Spain New Engineering Industry College Putian University Putian China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China

Quality assessment of electrocardiogram (ECG) signals holds significant importance in reducing the high-frequency false alarms in automated arrhythmia diagnosis. Existing quality assessment methods primarily rely on empirical threshold setting or the calculation of relevant statistical values to formulate decision rules. However, the thresholds set in this manner are typically based on experience and knowledge, resulting in decision rules that lack flexibility and struggle to adapt to changes in the dataset. To address this issue, many researchers have turned to deep learning algorithms for ECG signal quality assessment. Nevertheless, most existing deep learning methods usually require large-scale and labeled ECG data for training, whose acquiring is typically challenging. Therefore, this paper proposes an efficient method for ECG signal quality assessment. First, we use a contrast learning framework to construct sample pairs through multilevel data augmentation. Second, a densely connected convolutional network (DenseNet) is used to improve the model's ability of extracting local features in ECG signals, and a Squeeze-and-Excitation attention module is introduced to make the model pay more attention to critical features. Finally, the feature representation is learned by minimizing the contextual contrast loss to bring similar samples closer and push dissimilar samples farther away. In this way, we can utilize the contrastive learning framework to extract temporal representations from unlabeled data and transfer them to downstream ECG signal quality assessment tasks. Extensive experiments on the Physionet/CinC Challenge 2011 dataset demonstrate that our approach outperforms most existing quality assessment methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fault Detection via Occupation Kernel Principal Component Analysis

arXiv

引用

arXiv 2023年

作者： Morrison, Zachary Russo, Benjamin P. Lian, Yingzhao Kamalapurkar, Rushikesh The School of Mechanical and Aerospace Engineering Oklahoma State University StillwaterOK74074 United States The Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States The Automatic Laboratory Ecole Polytechnique Federale de Lausanne Lausanne1015 Switzerland

Reliable operation of automatic systems is heavily dependent on the ability to detect faults in the underlying dynamics. While traditional model-based methods have been widely used for fault detection, data-driven approaches have garnered increasing attention due to their ease of deployment and minimal need for expert knowledge. In this paper, we present a novel principal component analysis (PCA) method that uses occupation kernels. Occupation kernels result in feature maps that are tailored to the measured data, have inherent noise-robustness due to the use of integration, and can utilize irregularly sampled system trajectories of variable lengths for PCA. The occupation kernel PCA method is used to develop a reconstruction error approach to fault detection and its efficacy is validated using numerical simulations. © 2023, CC BY.

关键词： Fault detection

来源：评论

学校读者我要写书评

暂无评论

Static Force-Based Modeling and Parameter Estimation for a Deformable Link Composed of Passive Spherical Joints With Preload Forces

引用

IEEE/CAA Journal of automatica Sinica 2021年第11期8卷 1817-1826页

作者： Gaofeng Li Dezhen Song Lei Sun Shan Xu Hongpeng Wang Jingtai Liu Nankai University Tianjin 300350China Humanoids and Human Centered Mechatronics Research Line Italian Institute of Technology16163 GenovaItaly Department of Computer Science and Engineering Texas A&M UniversityCollege StationTexas 77843 USA Institute of Robotics and Automatic Information System Nankai UniversityTianjin 300350China Tianjin Key Laboratory of Intelligent Robotics Nankai UniversityTianjin 300350China

To balance the contradiction between higher flexibility and heavier load bearing capacity,we present a novel deformable manipulator which is composed of active rigid joints and deformable *** deformable link is composed of passive spherical joints with preload forces between socket-ball *** estimate the load bearing capacity of a deformable link,we present a static force-based model of spherical joint with preload force and analyze the static force propagation in the deformable *** yields an important result that the load bearing capacity of a spherical joint only depends on its radius,preload force,and static friction *** further develop a parameter estimation method to estimate the product of preload force and static friction *** experimental results validate our model.80.4%of percentage errors on the maximum payload mass prediction are below 15%.

关键词： Deformable link parameters identification spherical joint with preload force static force-based model

来源：评论

学校读者我要写书评

暂无评论

Sliding Mode Control for a DC-DC Buck Converter Feeding a Constant Power Load: A Practical Implementation

Sliding Mode Control for a DC-DC Buck Converter Feeding a Co...

引用

Advanced Technology in Electronic and Electrical engineering (ICATEEE), International Conference of

作者： Khalil Louassaa Aissa Chouder Mahdi Boukerdja Abdelhafid Cherifi Ali Aillane Electrical Engineering Department Electrical Engineering Laboratory University of M’sila M’sila Algeria Materials and Electronic Systems Laboratory University of Bordj Bou Arreridj Bordj Bou Arreridj Algeria Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (LabSTA) National School of Engineering of Sfax (ENIS) University of Sfax Sfax Tunisia

DC microgrids have gained in popularity in recent years due to features such as greater reliability, high efficiency, and control simplicity. Constant power loads (CPLs), on the other hand, are a problem and an effective cause of instability in DC MGs. To address the aforementioned issue, this paper discusses the stabilization of a buck power converter that supplies CPL via a regulated boost power converter. A robust sliding mode control is proposed, which stabilizes the output voltage and ensures the CPL's required power. The system is investigated in the context of external perturbations such as fluctuating input voltage and sudden change in the CPL. The robustness and efficacy of the proposed method have been demonstrated to confirm the system's overall stability. Simulation and experimentation are employed to verify the provided controller. The results verify the suggested controller's superiority.

关键词： Damping Voltage measurement Perturbation methods Microgrids Stability analysis Robustness Steady-state

来源：评论

学校读者我要写书评

暂无评论

Test Generation of Optical Logic Circuit Based on Binary Decision Diagram

Test Generation of Optical Logic Circuit Based on Binary Dec...

引用

2021 IEEE International Conference on Artificial Intelligence and computer Applications, ICAICA 2021

作者： Zhu, Aijun Song, Lei Niu, Junhao Hu, Cong Xu, Chuanpei Li, Zhi Guilin University of Electronic Technology School of Electronic Engineering and Automation Guilin541004 China Guangxi Key Laboratory of Automatic Detecting Technology and Instrument Guilin541004 China Department of Computer Science and Engineering Texas AandM University College StationTX77843 United States

ISBN: (纸本)9781665418676

With the breakthrough of silicon optical devices, optical network on chip has become a research hotspot. Optical logic circuit is the key unit that constitutes computing node in optical network on chip. Microring resonators (MRRs) are the basic components in optical logic circuits. However, due to the sensitivity of MRR to process drift and temperature, it is extremely prone to be faulty. Therefore, how to detect the optical logic circuit fault caused by MRRs is the key problem to improve its reliability. Firstly, the Binary Decision Diagram (BDD) of the fault-free and faulty circuit are established respectively;and then the BDD of the corresponding faulty circuit is constructed. The test BDD is obtained by XOR operation and simplification of the above two BDDs. The experimental results show the effectiveness of the proposed test generation based on BDD. © 2021 IEEE.

关键词： Timing circuits

来源：评论

学校读者我要写书评

暂无评论

Asymmetry of the Relative Entropy in the Regularization of Empirical Risk Minimization

arXiv

引用

arXiv 2024年

作者： Daunas, Francisco Esnaola, Iñaki Perlaza, Samir M. Vincent Poor, H. The Department of Automatic Control & Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom INRIA Centre Inria d'Université Côte d'Azur Sophia Antipolis06902 France The Department of Automatic Control and Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States The GAATI Mathematics Laboratory University of French Polynesia Fa'a'ā98702 French Polynesia

The effect of relative entropy asymmetry is analyzed in the context of empirical risk minimization (ERM) with relative entropy regularization (ERM-RER). Two regularizations are considered: (a) the relative entropy of the measure to be optimized with respect to a reference measure (Type-I ERM-RER);or (b) the relative entropy of the reference measure with respect to the measure to be optimized (Type-II ERM-RER). The main result is the characterization of the solution to the Type-II ERM-RER problem and its key properties. By comparing the well-understood Type-I ERM-RER with Type-II ERM-RER, the effects of entropy asymmetry are highlighted. The analysis shows that in both cases, regularization by relative entropy forces the solution's support to collapse into the support of the reference measure, introducing a strong inductive bias that can overshadow the evidence provided by the training data. Finally, it is shown that Type-II regularization is equivalent to Type-I regularization with an appropriate transformation of the empirical risk function. © 2024, CC BY.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Reduced Neural Network Based Ensemble Approach for Fault Detection and Diagnosis of Wind Energy Converter Systems

SSRN

引用

SSRN 2022年

作者： Mansouri, Majdi Dhibi, Khaled Bouzrara, Kais Nounou, Hazem Nounou, Mohamed Electrical and Computer Engineering Program Texas A&M University Qatar Qatar Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir 5019 Tunisia

Fault Detection and Diagnosis (FDD) is very important to achieve the best operation and ensure the safe and continuous operation of wind energy conversion (WEC) systems. Over the last decade, artificial neural networks surpass classical machine learning models in a variety of FDD tasks. On the other hand, ensemble learning (EL) techniques have gained significant attention from the scientific community. EL is a technique that creates and combines multiple machine learning models in order to produce one optimal predictive model which gives improved results. The goal of this paper is to develop and validate effective neural networks based ensemble approach. First, an ensemble classifier based on neural networks techniques and using bagging, boosting, and random subspace combination techniques is proposed. Second, an improved extension of the proposed neural networks-based ensemble technique is presented. The main idea behind this proposal is to determine variable relationships via a data-reduction framework using Hierarchical K-means (H-K-means) clustering method in order to overcome the problem of computation time and storage cost. Finally, the results obtained from the proposed neural networks-based ensemble techniques are compared with other ensemble and single machine learning methods to illustrate and validate the advantages of the proposed techniques. © 2022, The Authors. All rights reserved.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Comparison and analysis of two metaheuristic algorithms in the process of optimal reconfiguration of electricity networks with distributed generation: Case of RIN (Northern Interconnected Networks) Cameroon

Energy 360

引用

Energy 360 2025年 3卷

作者： Leger Nguewa Chuembou Felix Paune Pierre Kenfack Luc Vivien Assiene Mouodo University of Douala Laboratory for Computer and Automatic Engineering Cameroon University of Buea / College of Technology Buea. Cameroon

This article proposes a comparison of two meta-heuristic algorithms (genetic algorithm and bat algorithm) applied respectively to a highly densified IEEE-69 network, a moderately densified IEEE-33 network, and finally to the RIN (Northern Interconnected Networks) Cameroon with the aim of optimizing reconfiguration by integrating distributed generations (DG); thus providing a reduction in power losses with significant voltage stability. all this for 4 scenarios or operating cases for each network with an estimate of convergence performances and a comparison with current literature; the methodological approach presents modeling and simulations of the different stages of execution of the algorithms according to the nature of the loads connected to the distribution networks: constant power load (CP), constant current load (CI), constant impedance load (CZ), realistic load model (ZIP), and includes load growth. In the Matlab Simulink 2018.b environment; the results obtained for the case of RIN Cameroon with GA-ALGORITHME offer a reduction in power losses of 6.2669 %, with a power of 514.0293KW before reconfiguration and 481.8154 KW after reconfiguration. For a voltage 0.96824 Pu before reconfiguration and 0.9707 Pu after reconfiguration thus showing the efficiency and performance of the methods proposed in the optimization of the management of the reconfiguration of electrical networks. And above all a significant contribution in determining the DG of the RIN for optimization of the PDSE 2030 (2030 electricity sector development program) Cameroon.

关键词： Optimal Reconfiguration Network Distributed Generation Bat algorithm GA-ALGORITHM RIN Cameroon

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：