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2022 International Conference on Geographic Information and Remote Sensing technology, GIRST 2022

作者： Ding, Wenfei Li, Wen Ma, Dezhong Electronic Information Engineering Institute Harbin Huade University Harbin China College of Measurement-Control Technology & Communications Engineering Harbin University of Science & Technology Harbin China

ISBN: (纸本)9781510662186

As the basis of intelligent vehicle environment identification, street sign recognition is a necessary condition to assist safe driving. It is of great significance for realizing automatic driving, improving intelligent transportation system and promoting smart city construction. Traditional traffic sign recognition technology is limited for complex scenes, and the recognition effect is also affected by weather and light. The road sign recognition system based on deep learning includes street sign detection and street sign recognition. YOLOv3 deep learning object detection method is adopted for road sign detection, and CCTSDB standard data set is used as experimental data to perform operations such as region trimming, batch conversion of data format, BM3D noise reduction and image preprocessing and enhancement technology. 1800 images were selected to form the training set and test set, which ensured the high efficiency and timeliness of the road sign detection algorithm. The road sign recognition system adopts the image recognition method of Darknet-53, and the algorithm is optimized. The trained system is detected under the test of CCTSDB dataset, and the detection accuracy is over 97%, and the detection time reaches 0.021s. Therefore, the system meets the requirement of accurate real-time processing of traffic sign detection and recognition system. © 2023 SPIE.

关键词： Noise abatement

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Curve-Suppression-Based Event-Triggered Mechanisms for Quasi-Synchronization of Fuzzy Delayed Neural Networks on Time Scales

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3174-3187页

作者： Wan, Peng Zhou, Yufeng Zeng, Zhigang Lai, Jingang Wuhan University of Science and Technology School of Artificial Intelligence and Automation Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan430081 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent control of Education Ministry of China Wuhan430074 China

The vast majority of published event-triggered mechanisms (ETMs) are constructed based on measurement errors, which introduces a problem naturally that they are updated when the measurement errors exceed the thresholds although the current obtained sampling states can make systems converge well. With this problem in mind, we redesign ETMs for quasi-synchronization of T-S fuzzy neural networks (FNNs) with time delays on time scales. First, a novel ETM is designed for continuous-time FNNs with time-varying delays to achieve quasi-synchronization, with which synchronization errors is suppressed to globally exponentially converge to a ball. Second, we introduce the ETM for continuous-time FNNs to discrete-time FNNs, owing to the existence of discrete-time states, the Lypunov function of synchronization errors run over the exponentially decay curve, but it can be suppressed to evolve under another exponentially decay curve. Third, for FNNs on time scales with constant and time-varying delays, we estimate the forward jump operator of the Lyapunov functions and design ETMs to guarantee that the Lypunov functions evolve under the exponentially decay curves, so quasi-synchronization can be achieved. Last but not least, we prove that Zeno behavior will not happen and four numerical examples are introduced to verify the validity and the superiority of the proposed ETMs in reducing information transmission. © 2013 IEEE.

关键词： Continuous time systems

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Microwave Photonics-Based Small Hydrostatic Pressure Sensing Assisted by Convolutional Neural Network

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IEEE Sensors Journal 2025年第11期25卷 20948-20955页

作者： Li, Songlin Xue, Ting Wu, Yan Li, Zhuping Wu, Bin Tianjin University Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin300072 China Tianjin University State Key Laboratory of Precision Measuring Technology and Instruments Tianjin300072 China

Hydrostatic pressure measurement is essential in many industries, such as oil and gas production, chemical processing, and environmental monitoring. Due to the minimal impact of small hydrostatic pressure on ordinary silica optical fibers, research on its measurement utilizing optical fiber sensing technology remains limited. In this paper, a novel microwave photonics technique, termed optical carrier-based microwave interferometry (OCMI), is utilized for small hydrostatic pressure sensing with the assistance of a convolutional neural network (CNN). The theory of OCMI-based phase demodulation is established, and numerical simulations are conducted to investigate the factors affecting the axial displacement of the fiber core. In practical experiments, the phase demodulation method is applied to small hydrostatic pressure measurements;however, the results are suboptimal. Therefore, the CNN is developed to assist in the implementation of accurate small hydrostatic pressure sensing. The small hydrostatic pressures predicted by the well-trained CNN model are in good agreement with the actual values, with an error of less than 0.25 kPa. In addition, the prediction results from multiple Fabry-Perot interferometers demonstrate the feasibility and effectiveness of utilizing CNN for OCMI-based small hydrostatic pressure sensing. The introduction of machine learning broadens the application scope of the OCMI technique, allowing it to be employed for distributed sensing of a wider range of physical, chemical, and biological quantities. © 2001-2012 IEEE.

关键词： Interferometry

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Multi-Path Fusion Transformer Network for Hyperspectral Remote Sensing Image Classification

Multi-Path Fusion Transformer Network for Hyperspectral Remo...

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2024 International Conference on measurement, Communication, and Virtual Reality, MCVR 2024

作者： Li, Jiacheng Wang, Wei School of Measurement-Control Technology and Communication Engineering Harbin University of Science and Technology 52 Xuefu Road Heilongjiang Harbin150000 China

ISBN: (纸本)9781510691773

To address the challenges of insufficient spectral feature extraction and feature redundancy in hyperspectral image (HSI) classification, this paper proposes a Multi-Path Fusion Transformer Network (MPFT) that integrates Vision Transformer, hybrid residual convolution, and attention mechanisms. The proposed approach effectively utilizes both spatial and spectral information of pixels to overcome these limitations. The MPFT architecture comprises a Data Processing Module (DPM), a Dual-Stream Feature Extraction Module (DSFE), and a Vision Transformer (ViT) module. Specifically, the DPM performs dimensionality reduction and merges HSI information in three-dimensional space, while the DSFE extracts deeper features, which are subsequently processed by the ViT module for classification. Experiments conducted on three benchmark datasets—Indian Pines, University of Pavia, and Salinas—demonstrate that MPFT significantly outperforms mainstream models. Notably, MPFT achieved improvements in Overall Accuracy (OA) by up to 5.52%, Average Accuracy (AA) by up to 6.39%, and Kappa coefficient by up to 6.49% compared to state-of-the-art methods. These results highlight that MPFT not only efficiently extracts spatial-spectral features from HSI but also demonstrates superior effectiveness and robustness in various classification tasks. © 2025 SPIE.

关键词： Data streams

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Rapid stabilization of stochastic quantum systems in a unified framework

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Chinese Physics B 2023年第7期32卷 216-225页

作者：温杰王芳敏史元浩贾建芳曾建潮 School of Electrical and Control Engineering North University of ChinaTaiyuan 030051China State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijing 100084China School of Computer Science and Technology North University of ChinaTaiyuan 030051China

Rapid stabilization of general stochastic quantum systems is investigated based on the rapid stability of stochastic differential *** introduce a Lyapunov-LaSalle-like theorem for a class of nonlinear stochastic systems first,based on which a unified framework of rapidly stabilizing stochastic quantum systems is *** to the proposed unified framework,we design the switching state feedback controls to achieve the rapid stabilization of singlequbit systems,two-qubit systems,and N-qubit *** the unified framework,the state space is divided into two state subspaces,and the target state is located in one state subspace,while the other system equilibria are located in the other state *** the designed state feedback controls,the system state can only transit through the boundary between the two state subspaces no more than two times,and the target state is globally asymptotically stable in *** particular,the system state can converge exponentially in(all or part of)the state subspace where the target state is ***,the effectiveness and rapidity of the designed state feedback controls are shown in numerical simulations by stabilizing GHZ states for a three-qubit system.

关键词： rapid stabilization state feedback stochastic quantum systems switching control

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The exploration and the practice of engineering Education Certification and Talent Cultivation in the Context of New engineering-Analysis of Mechanical Design, Manufacturing and Automation Majors Based on Baicheng Normal University 24

The exploration and the practice of Engineering Education Ce...

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Education Digitalization and Computer Science, EDCS 2024

作者： Wang, Gang Ding, Simin Tan, Wenjun Wang, Yao Wang, Shuang Jing, Shufan School of Mechanical Engineering Jilin Communications Polytechnic Changchun130015 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China

ISBN: (纸本)9798400710360

In response to the problem that traditional mechanical majors cannot meet the talent cultivation needs under the background of "engineering education certification" and "new engineering subjects", this article takes the mechanical design and manufacturing and automation majors as an example to explore the upgrading and transformation of traditional majors, the reform of talent cultivation models, the new structure of curriculum system, and the construction of continuous improvement mechanisms. Firstly, with the integration of industry and education as the starting point, we will carry out a broad caliber and multi-level industrial robot talent training framework for win-win cooperation between schools and enterprises;Secondly, driven by subject competitions, we built a multidisciplinary integrated curriculum system with a dual spiral of curriculum and practice;Once more, basing on a multi-stage teaching and research team, we established a cross disciplinary and interdisciplinary teaching organization mechanism;Finally, we establish a multi-disciplinary, interdisciplinary, and multi-disciplinary training quality system for sustainable improvement through multiparty collaboration. After construction, our mechanical design, manufacturing, and automation major was awarded the provincial first-class major and the provincial undergraduate talent training and reform demonstration major in 2019, and was designated as the first batch of pilot majors for engineering education certification in the school. © 2024 Copyright held by the owner/author(s).

关键词： Curricula

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An improved leader follower formation control algorithm 10

An improved leader follower formation control algorithm

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10th International Conference on Mechanical engineering, Materials, and Automation technology, MMEAT 2024

作者： Wang, Gang Ding, Simin School of Mechanical Engineering Jilin Communications Polytechnic Changchun130015 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China

ISBN: (纸本)9781510682634

In response to the problem that the leader's dominant role in the leader follower formation control algorithm can easily lead to the failure of formation system control, in this paper, the artificial potential field method is used to improve the virtual leader formation algorithm to solve the formation problem. The concept of virtual navigators is used for formation control, while the artificial potential field method is used for obstacle avoidance tasks. The combination of the two effectively solves the problem of traditional formation control being prone to failure. Through comparative simulation, it is found that under the use of the improved algorithm in this paper, the formation motion trajectory is more stable, and the time for the relative position error of formation members to stabilize is shortened by 15 seconds, indicating that the formation control under the algorithm in this paper is more stable and efficient. © 2024 SPIE.

关键词： control systems Evolutionary algorithms Computer simulations Design Telecommunications Detection and tracking algorithms Error analysis Navigation systems Windows Reflection

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Design of Vehicle Bus Signal Simulation Device 5

Design of Vehicle Bus Signal Simulation Device

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5th International Conference on Sensing, measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Chen, Sirui Wang, Shiji Chen, Wenke Li, Baohua Qiao, Jiaqing School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Beijing Aerospace Measurement and Control Technology Co. Ltd Beijing China

ISBN: (纸本)9798331529192

As the functions of automobiles continue to increase and become more intelligent, the data exchange and communication between onboard electronic devices have become increasingly important. To ensure the reliability and stability of these systems in practical applications, it is necessary to manually simulate the testing and verification of ECUs with erroneous bus data packets. This paper designs a vehicular bus signal simulation device that can simulate the generation of CAN, LIN, FlexRay, CXPI, and SENT bus signals and their fault data packets. The hardware part of the device consists of an arbitrary waveform generator and an upper computer, while the software part uses QT to design the user interface and C++ to write the programmable software. Finally, experiments have verified the performance and accuracy of the simulation device. The waveforms captured by the digital storage oscilloscope are consistent with the expected input parameters, proving the effectiveness of the device. This device has significant application value in the development, teaching, and training of automotive electronic systems, capable of reducing the reliance on real-vehicle testing, and reducing test costs and time. © 2024 IEEE.

关键词： C++ (programming language)

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Fast resistivity imaging of transient electromagnetic using an extreme learning machine

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Soft Computing 2025年第2期29卷 1121-1131页

作者： Li, Ruiyou Zhang, Yong Li, Guang Li, Ruiheng Hu, Jia Li, Min School of Software and Internet of Things Engineering Jiangxi University of Finance and Economics NanChang330013 China School of Geophysics and Measurement Control Technology East China University of Technology NanChang330013 China School of Information Engineering Hubei University of Economics Wuhan430205 China The State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing University Chongqing400044 China

The transient electromagnetic method (TEM) is widely used in geophysical exploration. In TEM data interpretation, nonlinear inversion plays an important role. However, traditional TEM nonlinear inversion adopts the OCCAM imaging method, which merely presents the approximate shape of the stratum model, with poor inversion accuracy and much iteration time. To solve the above problems, a novel nonlinear inversion approach based on extreme learning machine (ELM) is proposed in this paper. The ELM is required to establish the input–output mapping relationship of the inversion network only once through the analytical method, which is different from the traditional neural network method that demands iterative gradient learning and is prone to fall into the local optimum. Moreover, the ELM inversion network by randomly assigning the hidden layer parameters is capable of mapping the observed TEM data and quickly producing resistivity images, which avoids time-consuming iteration and inversion calculations. The presented approach is applied to both synthetic and field examples. The results show that compared with the traditional nonlinear inversion algorithms (BP and OCCAM), the proposed method achieves better inversion accuracy and significantly reduces the calculation time, which verifies the effectiveness of the ELM algorithm for TEM data interpretation. Additionally, the research provides a new method and technology for TEM data inversion. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Electromagnetic transients

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A Spatial Modes Filtering FETD Method for 3-D Periodic Structures

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Applied Computational Electromagnetics Society Journal 2025年第2期40卷 96-102页

作者： Wang, Yixin Wei, Bing Fan, Kaihang He, Xinbo Zhao, Sihan Department of Information Technology Shaanxi Police College Xi’an710021 China School of Physics Xidian University Xi’an710071 China School of Information and Communications Engineering Xi’an Jiaotong University Xi’an710049 China Science and Technology on Electromechanical Dynamic Control Laboratory Xi’an710065 China

– A spatial modes filtering (SMF) finite-element time-domain (FETD) method with periodic boundary condition (PBC) is proposed for efficiently analyzing the electromagnetic characteristics of 3-D periodic structures with partial fine structures. The system matrices of FETD become asymmetrical because of the introduction of PBC, which prevents the system eigenvalue analysis. By decomposing the system matrix into PBC-independent and PBC-related parts, the unstable spatial modes under the given large time step can be found and removed from the symmetrical PBC-independent system matrices. Then the system matrix equation and time marching of the SMF-FETD and SMF-FETD method based on local eigenvalue solution (LES-SMF-FETD) with PBC are obtained. Numerical results illustrate the efficiency and effectiveness of the SMF-FETD method with PBC based on non-uniform mesh for analyzing the transport properties of 3-D periodic structures. © ACES.

关键词： Eigenvalues and eigenfunctions

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