检索结果-内蒙古大学图书馆

8th International Conference on control, Robotics and Cybernetics, CRC 2023

作者： Zheng, Shibo He, Kai Meng, Shuo Liu, Fangchencan Guo, Qiang Shenyang Jianzhu University School of Electrical and Control Engineering Shenyang City China Shenyang Jianzhu University School of Computer Science and Engineering Shenyang City China

ISBN: (纸本)9798350330588

In response to the problem of the filtering error of the CKF algorithm increasing linearly with the dimensionality of the state space, resulting in difficulty in propagating multiplicative noise, and the instability of the system caused by outliers in the system state driven model and observation data, this paper proposes an Extended Dimensional Embedded Cubature Kalman Filter algorithm based on the Truncated Singular Value Decomposition (TSVD-AECKF). Firstly, Singular Value Decomposition (SVD) is used instead of Cholesky Decomposition in the CKF algorithm to suppress the non-positivity of the system state covariance matrix;Considering the impact of small singular values on stability, this paper adopts the truncation method and provides a method for determining the truncation threshold;Secondly, the system noise is added to the state variable, and the embedded cubature criterion is used to improve the traditional CKF while expanding its dimensions;Finally, through simulation experiments, TSVD-AECKF was compared with other SLAM methods, and the results showed that this method can effectively suppress positioning errors that increase with the dimension of the state space, enhance the filter's ability to resist noise data interference, and thereby improve the robustness and stability of the mapping. © 2024 IEEE.

关键词： Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

Research on Optimization Method of Visual Odometer Based on Point Line Feature Fusion 23

Research on Optimization Method of Visual Odometer Based on ...

引用

7th International Conference on High Performance Compilation, Computing and Communications, HP3C 2023

作者： Zhang, Guoyin Yuan, Quande Liu, Yifan School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin China School of Computer Technology and Engineering Changchun Institute of Technology Jilin Changchun China

ISBN: (纸本)9781450399883

In low-texture-scenes, point feature based simultaneous location and map (SLAM) building algorithms are difficult to extract enough valid feature points, so that the SLAM system cannot work properly. To solve such problems, this paper proposes a visual SLAM algorithm for fusion of point and line features. On the basis of ORB point feature extraction, the LSD line feature algorithm is introduced and the extracted line segments are represented by the Plücker coordinate method. In the online feature matching stage, the LBD line segment descriptor is introduced, and the quadtree algorithm is used to avoid the concentration problem of point feature extraction. The progressive sampling uniformity (PROSAC) algorithm and geometric constraints are used to filter out incorrect matching of point line features, thereby improving positioning accuracy. Then, in the process of feature fusion, the idea of point line feature weighting is introduced to construct a new error function for point line fusion, minimizing the error function to obtain more accurate positioning information. Finally, the publicly available dataset was used to conduct experiments. © 2023 ACM.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Metaheuristic Optimization Algorithm for Signals Classification of Electroencephalography Channels

引用

computers, Materials & Continua 2022年第6期71卷 4627-4641页

作者： Marwa M.Eid Fawaz Alassery Abdelhameed Ibrahim Mohamed Saber Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Electronics and Communications Engineering Faculty of EngineeringDelta University for Science and TechnologyMansoura11152Egypt

Digital signal processing of electroencephalography(EEG)data is now widely utilized in various applications,including motor imagery classification,seizure detection and prediction,emotion classification,mental task classification,drug impact identification and sleep state *** the increasing number of recorded EEG channels,it has become clear that effective channel selection algorithms are required for various *** Whale Optimization Method(Guided WOA),a suggested feature selection algorithm based on Stochastic Fractal Search(SFS)technique,evaluates the chosen subset of *** may be used to select the optimum EEG channels for use in Brain-computer Interfaces(BCIs),the method for identifying essential and irrelevant characteristics in a dataset,and the complexity to be *** enables(SFS-Guided WOA)algorithm to choose the most appropriate EEG channels while assisting machine learning classification in its tasks and training the classifier with the ***(SFSGuided WOA)algorithm is superior in performance metrics,and statistical tests such as ANOVA and Wilcoxon rank-sum are used to demonstrate this.

关键词： Signals metaheuristics optimization feature selection multilayer perceptron support vector machines

来源：评论

学校读者我要写书评

暂无评论

EEG-based comparative measurement of visual fatigue caused by stereoscopic depth perception

EEG-based comparative measurement of visual fatigue caused b...

引用

The 2023 International Conference on Display Technology, (ICDT 2023)

作者： Jia, Lixiu Huang, Sheng Ding, Yiquan Feng, Lihang Huang, Xiaohua School of Computer Engineering Nanjing Institute of Technology Jiangsu Nanjing China School of Electrical Engineering and Control Science Nanjing Tech University Jiangsu Nanjing China

In this study, we investigated the influence of stereoscopic depth on visual fatigue based on subjective and EEG measurement. 19 channels of EEG data of 17 subjects before and after watching 3D movie with different depth ranges were recorded, and the power of δ, θ, α, β, power spectral parameters (gravity frequency, power spectral entropy) were calculated and analyzed. The results showed that visual fatigue caused by 3D enhanced movies with larger negative disparity was more significantly severe than that of 3D normal movies. © 2023, John Wiley and Sons Inc. All rights reserved.

关键词： Stereo image processing

来源：评论

学校读者我要写书评

暂无评论

Detuned Wireless Charging System with Constant Power Charging Ability and High-Misalignment Tolerance 7

Detuned Wireless Charging System with Constant Power Chargin...

引用

7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： He, Jiafang Ma, Jun Dong, Shuai Li, Zhenjie Harbin Institute of Technology Zhengzhou Research Institute Harbin Institute of Technology Harbin China Northeast Forestry University College of Computer and Control Engineering Harbin China

ISBN: (纸本)9798350359558

In practical applications, wireless charging systems (WCS) should solve unavoidable misalignment problems and realize stable output over a wide load range. Therefore, a detuned WCS with solid anti-misalignment capacity and constant power (CP) output over a wide load range using the overlapping coil magnetic coupler (OCMC) and Buck converter is proposed in this paper. First, the system structure is designed, and then the relationship between the mutual inductance, load resistance, and output power is investigated. Second, the detailed coupling characteristic of the optimized OCMC is analyzed. Finally, the closed-loop workflow of the WCS is described, and simulation results are given. © 2024 IEEE.

关键词： Inductance

来源：评论

学校读者我要写书评

暂无评论

Hier-EgoPack: Hierarchical Egocentric Video Understanding with Diverse Task Perspectives

arXiv

引用

arXiv 2025年

作者： Peirone, Simone Alberto Pistilli, Francesca Alliegro, Antonio Tommasi, Tatiana Averta, Giuseppe Department of Control and Computer Engineering Politecnico di Torino Italy

Our comprehension of video streams depicting human activities is naturally multifaceted: in just a few moments, we can grasp what is happening, identify the relevance and interactions of objects in the scene, and forecast what will happen soon, everything all at once. To endow autonomous systems with such a holistic perception, learning how to correlate concepts, abstract knowledge across diverse tasks, and leverage tasks synergies when learning novel skills is essential. A significant step in this direction is EgoPack, a unified framework for understanding human activities across diverse tasks with minimal overhead. EgoPack promotes information sharing and collaboration among downstream tasks, essential for efficiently learning new skills. In this paper, we introduce Hier-EgoPack, which advances EgoPack by enabling reasoning also across diverse temporal granularities, which expands its applicability to a broader range of downstream tasks. To achieve this, we propose a novel hierarchical architecture for temporal reasoning equipped with a GNN layer specifically designed to tackle the challenges of multi-granularity reasoning effectively. We evaluate our approach on multiple Ego4D benchmarks involving both clip-level and frame-level reasoning, demonstrating how our hierarchical unified architecture effectively solves these diverse tasks simultaneously. Project page: ***/hier-egopack. Copyright © 2025, The Authors. All rights reserved.

关键词： Multi-task learning

来源：评论

学校读者我要写书评

暂无评论

Clustering of Temperature Measurement Points for Key Components of Offshore Wind Turbines Considering Spatiotemporal Multi-Modality Characteristics 16

Clustering of Temperature Measurement Points for Key Compone...

引用

16th IEEE PES Asia-Pacific Power and Energy engineering Conference, APPEEC 2024

作者： Zhang, Yangyu Cheng, Yi Hu, Yang Fu, Daoyi Hu, Haopeng School of Control and Computer Engineering North China electric Power University Beijing China Haizhuang Windpower Equipment Co. Ltd. Chongqing China

ISBN: (纸本)9798350386127

The offshore environment is constantly changing and complex, causing changes in environmental temperature and operating conditions with seasonal variations, resulting in a spatiotemporal multimodal correlation between temperature measurement points of key components within wind turbines. A clustering method for temperature measurement points of key components of wind turbines based on Spearman correlation analysis and VGAE algorithm is proposed in this paper, which provides a reasonable modeling strategy for temperature characteristic perception modeling of offshore wind turbines. Analyze the raw data of wind turbines based on seasonal changes, generate spatiotemporal multimodal characteristic data, and use Spearman correlation coefficient to preliminarily analyze the nonlinear correlation of characteristic variables, defining the undirected graph relationship nodes for feature variable;Then, the potential feature dependencies and temperature variation characteristics of the undirected graph relationship nodes are excavated, and the Variational graph auto encoders algorithm is used. The encoder composed of GCN and variational inference method are used to analyze the potential representations and reconstruct the undirected graph relationship nodes;Finally, the K-means clustering method is used to cluster the temperature measurement points of key components of offshore wind turbines. The results indicate the effectiveness of the method. © 2024 IEEE.

关键词： Offshore wind turbines

来源：评论

学校读者我要写书评

暂无评论

Benchmarking Semantic Communications for Image Transmission Over MIMO Interference Channels 16

Benchmarking Semantic Communications for Image Transmission ...

引用

16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Wang, Yanhu Guo, Shuaishuai Dong, Anming Zhao, Hui School of Control Science and Engineering Shandong University China School of Computer Science and Technology Qilu University of Technology China Eurecom Communication Systems Department France

ISBN: (纸本)9798350390643

Semantic communications offer promising prospects for enhancing data transmission efficiency. However, existing schemes have predominantly concentrated on point-to-point transmissions. In this paper, we aim to investigate the validity of this claim in interference scenarios compared to baseline approaches. Specifically, our focus is on general multiple-input multiple-output (MIMO) interference channels, where we propose an interference-robust semantic communication (IRSC) scheme. This scheme involves the development of transceivers based on neural networks (NNs), which integrate channel state information (CSI) either solely at the receiver or at both transmitter and receiver ends. Moreover, we establish a composite loss function for training IRSC transceivers, along with a dynamic mechanism for updating the weights of various components in the loss function to enhance system fairness among users. Experimental results demonstrate that the proposed IRSC scheme effectively learns to mitigate interference and outperforms baseline approaches, particularly in low signal-tonoise (SNR) regimes. © 2024 IEEE.

关键词： Radio transceivers

来源：评论

学校读者我要写书评

暂无评论

On the Fault Tolerance of Self-Supervised Training in Convolutional Neural Networks

On the Fault Tolerance of Self-Supervised Training in Convol...

引用

IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Rosario Milazzo Vincenzo De Marco Corrado De Sio Sophie Fosson Lia Morra Luca Sterpone Department of Control and Computer Engineering Polytechnic of Torino Italy

Deep neural networks (DNNs) are increasingly used in critical applications from healthcare to autonomous driving. However, their predictions were shown to degrade in the presence of transient hardware faults, leading to potentially catastrophic and unpredictable errors. Consequently, several techniques have been proposed to increase the fault tolerance of DNNs by modifying network structures and/or training procedures, thereby reducing the need for costly hardware redundancy. There are, however, design or training choices whose impact on fault propagation has been overlooked in the literature. In particular, self-supervised learning (SSL), as a pretraining technique, was shown to improve the robustness of the learned features, resulting in better performance in downstream tasks. This study investigates the fault tolerance of several SSL techniques on image classification benchmarks, including several related to Earth Observation. Experimental results suggests that SSL pretraining, alone or in combination with fault mitigation techniques, generally improves DNNs' fault tolerance, although the performance gap vary among datasets and SSL techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dynamic Feature Point Elimination Algorithm Based on YOLOv5 and Optical Flow Method 23

Dynamic Feature Point Elimination Algorithm Based on YOLOv5 ...

引用

7th International Conference on High Performance Compilation, Computing and Communications, HP3C 2023

作者： Liu, Yifan Yuan, Quande Zhang, Guoyin School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin China School of Computer Technology and Engineering Changchun Institute of Technology Jilin Changchun China

ISBN: (纸本)9781450399883

In traditional visual simultaneous localization and mapping (vSLAM) systems, feature points are critical for feature matching and pose estimation. However, visual odometry keyframes often contain many dynamic points, which can adversely affect the accuracy of the SLAM system. To address this issue, this paper proposes a dynamic feature point elimination algorithm based on the YOLOv5 target detection network and optical flow method using image processing techniques. Specifically, the YOLOv5 network is used to identify regions in the image that may contain dynamic objects, which are then divided into sub-regions. Depth information from the depth image and feature points from the dynamic regions are used to obtain feature points with depth information. These feature points are then clustered using the GMM clustering algorithm, and dynamic feature points are eliminated based on the clustering results. Experimental results show that the proposed algorithm effectively eliminates dynamic points in the image, thus improving the accuracy of the SLAM system. © 2023 ACM.

关键词： Optical flows

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：