检索结果-内蒙古大学图书馆

Actively tunable dual-broadband graphene-based terahertz metamaterial absorber

Chinese Physics B 2021年第12期30卷 495-502页

作者： Dan Hu Tian-Hua Meng Hong-Yan Wang Mai-Xia Fu School of Physics and Electrical Engineering Anyang Normal UniversityAnyang 455000China Department of Physics and Electronics Science Shanxi Datong UniversityDatong 037009China School of Education Information Technology and Communication Anyang Normal UniversityAnyang 455000China College of Information Science and Engineering Henan University of TechnologyKey Laboratory of Grain Information Processing and ControlMinistry of EducationZhengzhou 450001China

A tunable metamaterial absorber(MA)with dual-broadband and high absorption properties at terahertz(THz)frequencies is designed in this *** MA consists of a periodic array of flower-like monolayer graphene patterns at top,a SiO_(2)dielectric spacer in middle,and a gold ground plane at the *** simulation results demonstrate that the designed MA has two wide absorption bands with an absorption of over 90%in frequency ranges of 0.68 THz-1.63 THz and 3.34 THz-4.08 THz,and the corresponding relative bandwidths reach 82.3%and 20%,*** peak absorptivity of the absorber can be dynamically controlled from less than 10%to nearly 100%by adjusting the graphene chemical potential from 0 eV to 0.9 ***,the designed absorber is polarization-insensitive and has good robustness to incident *** a high-performance MA has broad application prospects in THz imaging,modulating,filtering,etc.

关键词： metamaterial graphene absorber terahertz

来源：评论

学校读者我要写书评

暂无评论

Secure Beamforming Design for IRS-ISAC Systems with a Hardware-Efficient Hybrid Beamforming Architecture

引用

IEEE Transactions on Vehicular technology 2025年

作者： Xiong, Weijie Zhao, Zhenglan Lin, Jingran Xiao, Zhiling Li, Qiang University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100083 China Tianfu Jiangxi Laboratory Sichuan Chengdu641419 China

In this paper, we employ a hardware-efficient hybrid beamforming (HB) architecture to achieve balanced performance in an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system. We consider a scenario where a multi-antenna, dual-function base station (BS) performs secure beamforming for a multi-antenna legitimate receiver while simultaneously detecting potential targets. Our objective is to maximize the communication secrecy gap by jointly optimizing the analog and digital beamformers, IRS reflection coefficients, and radar scaling factor, subject to constraints on beampattern similarity, total transmit power budget, and the constant modulus of both the analog beamformer and IRS reflection coefficients. This secrecy gap maximization problem is generally non-convex. To address this, we incorporate the exterior penalty method by adding the radar constraint as a penalty term in the objective function. We then propose an efficient approach based on the penalty dual decomposition (PDD) framework to solve the reformulated problem, featuring closed-form solutions at each step and guaranteeing convergence to a stationary point. Simulation results validate the effectiveness of the proposed algorithm and demonstrate the superiority of the IRS-ISAC system with HB architecture in balancing performance and hardware costs. © 1967-2012 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Anomaly Score Rank Based Unsupervised Sample Selection Method

SSRN

引用

SSRN 2024年

作者： He, Zhonghai Du, Yinzhi Feng, Zhanbo Zhang, Xiaofang School of Control Engineering Northeastern University at Qinhuangdao Hebei Province Qinhuangdao066004 China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China School of Optics and Photonics Beijing Institute of Technology Beijing China

The process of selecting representative samples is crucial for establishing an accurate calibration model. To enhance the representativeness of the samples, a method for sample selection, utilizing the degree of anomaly as the evaluation criterion, is proposed. Initially, anomaly scores corresponding to various detection methods are obtained to ensure a comprehensive evaluation. These scores are then normalized by the confidence lower limit to establish a consistent scoring criterion. Subsequently, the weights of different detection methods are determined through eigenvector centrality analysis of a graph, where the methods serve as nodes and the similarity acts as weighted edges. Finally, the comprehensive anomaly scores are computed as the sum of weighted scores and are subsequently sorted. Representative samples are selected using a uniformly-spaced sampling approach, with the spacing determined by a predefined and provided sample number. The efficacy of the method is validated across different sample sets. © 2024, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Polarization-Space-Time Processing in Mainlobe Blanket Jamming via CP Decomposition

Polarization-Space-Time Processing in Mainlobe Blanket Jammi...

引用

IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Bunian Pan Bing Wang Luxin Dong Xue Yao Xianxiang Yu Guolong Cui School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Electronic Information Control Laboratory Chengdu China School of Information Science and Engineering Southeast University Nanjing China

This paper deals with the problem of mainlobe jamming suppression for phased-array radar system via a joint polarization-space-time processing method resorting to tensor decomposition. Firstly, a dual-polarization receiving array model is established. Then, base on the polarization-space-time characteristics, CANDECOMP/PARAFAC (CP) decomposition is leveraged to recast the received signals as a third-order tensor consisting of three factor matrices. Further, the target echo and the jamming signal can be obtained via minimizing the Frobenius norm of the approximation error between the factor matrices and their iteration forms. Finally, the effectiveness of the proposed method by numerical simulation is verified, showing its capability to resist mainlobe jamming compared with the art competing method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Routing Algorithm Based on Obstacle-Avoiding Rectilinear Steiner Minimum Tree for Three-Dimensional System in Package

SSRN

引用

SSRN 2024年

作者： Li, Zhensong Wen, Hao Wang, Yuduo Key Laboratory of Information and Communication Systems Ministry of Information Industry Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing102206 China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing102206 China Beijing Information Science and Technology University China

In view of the routing stage of very large scale integration circuit(VLSI), it is essential to construct the obstacle-avoiding rectilinear Steiner minimum tree(OARSMT) quickly and efficiently. For three-dimensional System in Package(SiP), the routing stage is an critical problem that cannot be done efficiently by commercial electronic design automation(EDA) software. In this paper, single-layer OARSMT(SL-OARSMT) and three- dimensional OARSMT (3D-OARSMT) routing algorithms are proposed to complete routing stage in three-dimensional integration system. In the SL-OARSMT, the obstacle-avoiding spanning graph (OASG) is constructed and the multi-terminal spanning tree(MTST) is built and converted into a pin spanning tree(PST) by removing all the not-pin point from MTST. Then the rectilinear Steiner minimum tree(RSMT) is generated and legalized to get the legal routing solution for single routing layer. Multi-segment-edge global optimization and V-type local optimization are adopted to achieve minimum routing length. The 3D-OARSMT is formed by combing SL-OARSMT and through silicon vias(TSVs）location insertion so that can handle the inter-layer routing in 3D integrated circuit. Experiments results shows that the SL-OARSMT algorithm achieves 2%~5% entire routing length reduction comparing to recent research competitor and makes the single layer routing more efficiency. For the 3D-OARSMT, the TSV number needed for inter-layer routing is significantly reduced and this algorithm provides a feasible solution for 3D SiP routing. © 2024, The Authors. All rights reserved.

关键词： System-in-package

来源：评论

学校读者我要写书评

暂无评论

Automatic Face Expression Neutralisation and Posture Correction via 3D Contrastive Learning

引用

Procedia Computer Science 2023年 225卷 269-278页

作者： Grina Wiem Douik Ali University of Sousse Networked Objects Control and Communication Systems Laboratory National School of Engineers of Sousse Sousse Technology Center Sahloul Belt Road 4054 University of Monastir National Engineering School of Monastir Rue Ibn Jazzar Monastir 5035 Tunisia University of Sousse Networked Objects Control and Communication Systems Laboratory National School of Engineers of Sousse Sousse Technology Center Sahloul Belt Road 4054 Tunisia

The performance of recognition systems can be significantly affected by various factors, with facial expression poses and lighting changes being the main confounding factors. In order to minimize their impact, we propose an intriguing method in this study that enables the generation of high-quality images specifically tailored to the target domain. Our objective is to utilize disentangled representation to effectively model the decomposition of data variations and generate neutral facial expression images with frontal posture and adaptive illumination. To achieve this, we incorporate 3D priors in the adversarial learning during the training process, simulating the generation of an analytical 3D face deformation as well as rendering operations. Additionally, we employ contrastive learning to control the disentanglement of the generated faces while preserving the essential properties of facial features. This technique enables us to learn an embedding space in which similar data samples are represented closely, while distinct samples are kept far apart from each other. Furthermore, we conduct an analysis of the learned latent space and introduce several other significant properties that enhance the reinforcement of factor disentanglement. These properties include an imitation learning algorithm, which facilitates the acquisition of meaningful patterns and characteristics.

关键词： generative adversarial network expression neutralization disentanglement 3D contrastive learning

来源：评论

学校读者我要写书评

暂无评论

Sensing With Random communication Signals

arXiv

引用

arXiv 2025年

作者： Lu, Shihang Liu, Fan Xiong, Yifeng Du, Zhen Cui, Yuanhao Li, Shuangyang Yuan, Weijie Yang, Jie Jin, Shi National Mobile Communications Research Laboratory Southeast University Nanjing210096 China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing210044 China Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin10587 Germany Southern University of Science and Technology Shenzhen518055 China Frontiers Science Center for Mobile Information Communication and Security and also The Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing211189 China

communication-centric Integrated Sensing and communication (ISAC) has been recognized as a promising methodology to implement wireless sensing functionality over existing network architectures, due to its cost-effectiveness and backward compatibility to legacy cellular systems. However, the inherent randomness of the communication signal may incur huge fluctuations in sensing capabilities, leading to unfavorable detection and estimation performance. To address this issue, we elaborate on random ISAC signal processing methods in this article, aiming at improving the sensing performance without unduly deteriorating the communication functionality. Specifically, we commence by discussing the fundamentals of sensing with random communication signals, including the performance metrics and optimal ranging waveforms. Building on these concepts, we then present a general framework for random ISAC signal transmission, followed by an in-depth exploration of time-domain pulse shaping, frequency-domain constellation shaping, and spatial-domain precoding methods. We provide a comprehensive overview of each of these topics, including models, results, and design guidelines. Finally, we conclude this article by identifying several promising research directions for random ISAC signal transmission. © 2025, CC BY-SA.

关键词： Signaling

来源：评论

学校读者我要写书评

暂无评论

FFGAN: An Auto-supervised Approach for Frontal Face Generation Via Disentangled Contrastive Learning

引用

Procedia Computer Science 2024年 246卷 3644-3653页

作者： Grina Wiem Douik Ali National Engineering School of Monastir University of Monastir Rue Ibn Jazzar 5035 Monastir Tunisia Networked Objects Control and Communication Systems Laboratory Sousse Technology Centre National School of Engineers of Sousse University of Sousse Sahloul Belt Road 4054 Sousse Tunisia

This work proposes a novel generative model, FF-GAN (Frontal Face Generative Adversarial Network), for generating high-quality and diverse frontal faces. FF-GAN utilizes contrastive learning to effectively learn the underlying representation of frontal faces from unlabeled image datasets. This approach allows the model to capture the essential characteristics of frontal faces without the need for explicit pose annotations. We evaluate the performance of FF-GAN using established metrics like FID (Fréchet Inception Distance), IS (Inception Score), and SSIM (Structural Similarity Index Measure). The results demonstrate that FF-GAN achieves superior performance compared to existing methods, generating highly realistic and visually appealing frontal faces with exceptional structural coherence. This research contributes to the field of facial image generation by introducing an effective unsupervised learning approach based on contrastive learning for generating high-quality frontal faces.

关键词： Unsupervised Facial Pose Analysis Contrastive Learning Disentanglement Pose Estimation

来源：评论

学校读者我要写书评

暂无评论

Threshold Selection for Circuit Board Nodes Based on LSTM Method

Threshold Selection for Circuit Board Nodes Based on LSTM Me...

引用

Intelligent control, measurement and Signal Processing and Intelligent Oil Field (ICMSP), International Conference on

作者： Huimin Liu Fangxing Lv Jingjing Liu Xi'an Shiyou University Xi'an China School of Electronic Engineering Xi'an Shiyou University Xi'an China Key Laboratory of Oil and Gas Well Measurement and Control Technology Shaanxi Province Xi'an China

ISBN: (数字)9798331516550

ISBN: (纸本)9798331516567

With the advancement of modern electronic integration technology, the complexity of circuit board composition has significantly increased, making fault detection more challenging. This study proposes a fault diagnosis method based on the current and voltage test values of circuit nodes. By setting up test points on the circuit board, the method determines whether the board is functioning correctly by evaluating if the test values fall within the specified thresholds. Leveraging existing circuit board test data, the study first performs data cleansing, followed by sliding window processing. Long Short-Term Memory (LSTM) networks are then employed to predict the test values for each window, and the 3σ method is used for conditional judgment to derive appropriate thresholds. This approach enhances detection accuracy and the ability to identify subtle anomalies, thereby significantly improving the reliability and precision of circuit board fault detection without damaging the circuit board.

关键词： Fault diagnosis Accuracy Fault detection Printed circuits Neural networks Signal processing Electrical fault detection Threshold voltage Integrated circuit reliability Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Automatic location of surface-monitored microseismicity with deep learning

引用

Earthquake Research Advances 2025年第2期5卷

作者： Gan, Zhaolong Tian, Xiao Zhang, Xiong Dai, Mengxue Engineering Research Center for Seismic Disaster Prevention and Engineering Geological Disaster Detection of Jiangxi Province (East China University of Technology) Nanchang 330013 China School of Geophysics and Measurement-Control Technology East China University of Technology Nanchang 330013 China

Accurate and rapid determination of source locations is of great significance for surface microseismic monitoring. Traditional methods, such as diffraction stacking, are time-consuming and challenging for real-time monitoring. In this study, we propose an approach to locate microseismic events using a deep learning algorithm with surface data. A fully convolutional network is designed to predict source locations. The input data is the waveform of a microseismic event, and the output consists of three 1D Gaussian distributions representing the probability distribution of the source location in the x, y, and z dimensions. The theoretical dataset is generated to train the model, and several data augmentation methods are applied to reduce discrepancies between the theoretical and field data. After applying the trained model to field data, the results demonstrate that our method is fast and achieves comparable location accuracy to the traditional diffraction stacking location method, making it promising for real-time microseismic monitoring. © 2024 China Earthquake Networks Center.

关键词： Deep learning Microseismic monitoring Source location

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：