检索结果-内蒙古大学图书馆

Experimental demonstration of 220-GHz terahertz signals wireless transmission over 4.6 km

science China(information sciences) 2025年第1期68卷 386-388页

作者： Yi WEI Jianjun YU Mingxu WANG Xiongwei YANG Qiutong ZHANG Jingwen TAN Bing ZHANG Ying WU Yang HAN Peng TIAN Wen ZHOU Kaihui WANG Feng ZHAO State Key Laboratory of ASIC and System Key Laboratory for Information Science of Electromagnetic Waves (MoE)School of Information Science and Technology Fudan University School of Electronic Engineering Xi'an University of Posts and Telecommunications

The advancement of terahertz (THz) communication technology drives the evolution of wireless communication systems,offering novel pathways and technical means for the development of future 6G communication *** wireless communication systems are often constrained by bandwidth limitations of electronic devices in high frequency ***,THz communication technology leverages the characteristics of electromagnetic waves to transcend these limitations,enabling communication athigher frequencies and wider bandwidths.

关键词： wireless terahertz over demonstration experimental signals transmission

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based LPI radar signals analysis and identification using a Nyquist Folding Receiver architecture

引用

Defence technology（防务技术） 2023年第1期19卷 196-209页

作者： Tao Wan Kai-li Jiang Hao Ji Bin Tang School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu611731China

Nyquist Folding Receiver(NYFR)is a perceptron structure that realizes a low probability of intercept(LPI)signal analog to *** at the problem of LPI radar signal receiving,the time domain,frequency domain,and time-frequency domain problems of signals intercepted by NYFR structure are *** with the time-frequency analysis(TFA)method,a radar recognition scheme based on deep learning(DL)is introduced,which can reliably classify common LPI radar ***,the structure of NYFR and its characteristics in the time domain,frequency domain,and time and frequency domain are ***,the received signal is then converted into a time-frequency image(TFI).Finally,four kinds of DL algorithms are used to classify LPI radar *** results demonstrate the correctness of the NYFR structure,and the effectiveness of the proposed recognition method is verified by comparison experiments.

关键词： Nyquist folding receiver Ultra-wideband Deep learning Time-frequency analysis Identification Classification

来源：评论

学校读者我要写书评

暂无评论

Finite-time fault-tolerant control of attitude control system of quadrotor UAV based on neural network disturbance observer

引用

Neural Computing and Applications 2025年第7期37卷 5597-5606页

作者： Li, Boning Chen, Ming Qi, Shuchang Peng, Kaixiang School of Electronic and Information Engineering University of Science and Technology Liaoning Liaoning Anshan China School of Automation University of Science and Technology Beijing Beijing China

This paper investigates a new finite-time fault-tolerant control scheme for a quadrotor unmanned aerial vehicle (UAV). Firstly, a novel neural network disturbance observer with an auxiliary system is designed to compensate for actuator faults and external disturbances. In addition, in order to ensure the system’s rapidity, the finite-time theory is incorporated into the observer design and the controller design. The hyperbolic tangent function is also introduced to process the input signals, which ensures that the UAV receives relatively the smooth input signals. The design scheme takes into account the rapidity and robustness of the system, which makes the performance of the UAV better. Finally, the advantages of the proposed scheme are demonstrated through comparative experiments and the feasibility of the scheme is further verified through actual physical experiments. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Hyperbolic functions

来源：评论

学校读者我要写书评

暂无评论

SET-MRTS:An Empirical Experiment Tool for Real-Time Scheduling and Synchronization

引用

Journal of electronic science and technology 2022年第1期20卷 30-42页

作者： Ze-Wei Chen Hang Lei Mao-Lin Yang Yong Liao School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610054

In the real-time scheduling theory,schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols,respectively,and the empirical synthesis experiment is one of the major methods to compare the performance of such ***,since many sophisticated techniques have been adopted to improve the analytical accuracy,the implementation of such analyses and experiments is often *** paper proposes a schedulability experiment toolkit for multiprocessor real-time systems(SET-MRTS),which provides a framework with infrastructures to implement the schedulability and synchronization analyses and the deployment of empirical synthesis ***,with well-designed peripheral components for the input and output,experiments can be conducted easily and flexibly on *** demonstration further proves the effectiveness of SET-MRTS in both functionality and availability.

关键词： Experiment real-time system schedulability software tools synchronization

来源：评论

学校读者我要写书评

暂无评论

Adaptive Output-Feedback Prescribed Performance Control of Uncertain Switched Nonlinear Systems

引用

IAENG International Journal of Applied Mathematics 2024年第1期54卷 140-148页

作者： Ouyang, Xinyu Zhang, Feng Zhao, Nannan School of Electronic and Information Engineering University of Science and Technology Liaoning Liaoning CO Anshan114051 China School of Electronic and Information Engineering University of Science and Technology Liaoning Liaoning AnshanCO114051 China

Adaptive Output-feedback prescribed performance control (PPC) scheme is investigated for a class of uncertain switched nonlinear systems. Compared with the existing methods, this paper designs a new type of error transformation function. Its advantage is that based solely on the properties of the function, the output error can be constrained within the preset band without any additional conditions. Neural networks are used to approach unknown nonlinearities in switched systems, and state observers are used to estimate unknown states. The stability analysis shows that the proposed method ensures that all closed-loop signals are bounded and the tracking error can converge to the adjustable constraint function under the switching condition of average dwell time. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments. © 2024, International Association of Engineers. All rights reserved.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

MRLKG: Multimodal Representation Learning with Keyword-Based Graph for Hashtag Recommendation 7

MRLKG: Multimodal Representation Learning with Keyword-Based...

引用

7th International Conference on Machine Learning and Natural Language Processing, MLNLP 2024

作者： Yasir Khalil, Mian Muhammad Wang, Qingxian Chen, Bo Rauf, Muhammad Arslan Wang, Weidong School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350354973

The increasing volume of social media content has made hashtag recommendation a critical task for enhancing content discoverability and user engagement. This paper presents MRLKG (Multimodal Representation Learning with Keywordbased Graph) for hashtag recommendation. Our approach integrates cross-modality joint representation with a keyword-guided graph. The joint embedding provides a contextually rich representation of the content. In parallel, a keyword-guided Graph Convolutional Network (GCN) generates a refined representation of each microblog post content by emphasizing key concepts and their relational context with other microblog posts, essential for understanding the broader context and trends that hashtags often represent. By integrating the contextually rich joint embedding provided by transformers with the KeyBERT-GCN's focus on key concepts and their relational structure, the model can recommend hashtags that are both contextually relevant and aligned with the key trends represented by other microblog posts. Experimental results demonstrate the effectiveness of our method, showing improved performance over existing approaches. This method offers a robust solution for hashtag recommendation by leveraging both contextual understanding and graph-based reasoning. © 2024 IEEE.

关键词： Graph embeddings

来源：评论

学校读者我要写书评

暂无评论

NNC: A Nearest Neighbors Constraint-based Metric Learning for Multivariate Time Series Classification 2

NNC: A Nearest Neighbors Constraint-based Metric Learning fo...

引用

2nd IEEE International Conference on Signal, information and Data Processing, ICSIDP 2024

作者： Chen, Zhi Zhang, Fengli Zhu, Jiajing Zhang, Yun Li, Qiaoqin Liu, Yongguo University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China

ISBN: (纸本)9798331515669

Multivariate time series (MTS) classification has gained significant attention as a prominent research area in recent years. Studies using Mahalanobis distance-based dynamic time warping along with metric learning algorithms have reported significant results. Existing metric learning approaches, such as large margin nearest neighbor, seek to optimize a loss function with two components: one that reduces the distance between samples with the same label and another that increases the distance between samples with different labels. However, these two terms play an opposite role in some situations and it is difficult to explore a way to balance such two competitive terms. In this paper, we introduce a nearest neighbors constraint (NNC) model designed for MTS classification. In NNC, a data-adaptive Mahalanobis distance-based dynamic time warping distance metric is designed to compute the distance between two MTS. To learn the Mahalanobis distance, a concise and effective loss function is developed. Instead of scanning all triplets, NNC only employs the triplets which violate the rule that an MTS's k nearest neighbors should share the same label with it to learn the Mahalanobis distance. Experiments on 9 public MTS datasets demonstrate that the proposed model achieves competitive performance. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

AOA Based Localization and orientation estimation of UWB via Weighted Least Squares 24

AOA Based Localization and orientation estimation of UWB via...

引用

24th IEEE International Conference on Communication technology, ICCT 2024

作者： Zhang, Di Li, Ye Yin, Guangqiang University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China

ISBN: (纸本)9798350363760

In the Internet of Things (IoT), robot localization using ultra-wideband (UWB) technology requires estimating both the position and orientation of the robot. However, current localization and orientation estimation methods often rely on rigid body models, which require multiple anchors, leading to high system costs. To address this limitation, this paper focuses a self-localization approach based on the angle of arrival (AOA), which reduces complexity with only a single anchor. We propose an enhanced algorithm that employs weighted least squares (WLS) to improve estimation accuracy. Additionally, we derive the closed-form Cramér-Rao lower bound (CRLB) as a theoretical benchmark to evaluate the performance of the proposed algorithm. Both simulation results and real-world experiments demonstrate that the proposed algorithm achieves high localization accuracy, providing a cost-effective and efficient solution for IoT applications. © 2024 IEEE.

关键词： Ultra-wideband (UWB)

来源：评论

学校读者我要写书评

暂无评论

Digital twin empowered cooperative trajectory planning of platoon vehicles for collision avoidance with unexpected obstacles

引用

Digital Communications and Networks 2024年第6期10卷 1666-1676页

作者： Hao Du Supeng Leng Jianhua He Kai Xiong Longyu Zhou School of Information&Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China School of Computer Science and Electronic Engineering University of EssexColchester CO43SQUnited Kingdom Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 518110China

Road obstacles that unexpectedly appear due to vehicle breakdowns and accidents are major causes of fatal road *** Autonomous Vehicles(CAVs)can be used to avoid collisions to ensure road safety through cooperative sensing and ***,the collision avoidance performance of CAVs with unexpected obstacles has not been studied in the existing *** this paper,we first design a platoon-based collision avoidance framework for *** this framework,we deploy a Digital Twin(DT)system at the head vehicle in a platoon to reduce communication overhead and decision-making delay based on a proposed trajectory planning *** addition,a DT-assistant system is deployed on the assistant vehicle to monitor vehicles out of the sensing range of the head vehicle for the maintenance of the DT *** this case,the transmission frequency of kinetic states of platoon members can be reduced to ensure low-overhead ***,we design a variable resource reservation interval that can ensure DT synchronization between DT and the assistant system with high *** further improve road safety,an urgency level-based trajectory planning algorithm is proposed to avoid unexpected obstacles considering different levels of emergency *** results show that our DT system-based scheme can achieve significant performance gains in unexpected obstacle *** to the existing schemes,it can reduce collisions by 95%and is faster by about 10%passing by the unexpected obstacle.

关键词： Platoon driving Cooperative trajectory planning Digital twin Obstacle avoidance

来源：评论

学校读者我要写书评

暂无评论

Improving the Inference Efficiency of Transformer Models in Machine Translation Tasks by Low-rank Decomposition Methods

Improving the Inference Efficiency of Transformer Models in ...

引用

2024 International Conference on electronics and Devices, Computational science, ICEDCS 2024

作者： Liu, Zhijia University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China

ISBN: (纸本)9798331527624

In recent years, Transformer model has made remarkable progress in machine translation tasks and has become the mainstream translation model. However, the calculation complexity of Transformer model is high, especially when dealing with long sequences, the inference efficiency becomes a key issue. In order to improve the inference efficiency of Transformer model, a method based on low-rank decomposition is adopted, and the calculation amount is significantly reduced by optimizing the key modules of the model. Firstly, this paper decomposes the self-attention mechanism in the Transformer model into low-rank, and decomposes the high-dimensional matrix into the product of several low-dimensional matrices by using matrix decomposition technology, thus reducing the computational complexity. Secondly, in the process of model training, pruning technology is combined to remove redundant parameters, so as to further reduce the calculation amount and model scale. On the premise of ensuring the translation quality, this paper carries out experimental verification on large-scale data sets, and the results show that this method can greatly improve the inference speed of the model while maintaining the translation performance. For short sentences with less than 100 words, the inference time of the original model is from 50 milliseconds to 140 milliseconds, and the inference time of the low-rank decomposition model is shortened to 40-100 milliseconds, which is a significant improvement for the real-time translation system. The experimental results show that the low-rank decomposition method not only significantly improves the inference efficiency of the model, but also effectively reduces the consumption of computing resources, which provides a more economical and efficient choice for practical application. © 2024 IEEE.

关键词： Computer aided language translation

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：