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Advances in Transportation Studies 2024年第Speical issue期1卷 115-124页

作者： Yang, X.W. School of Information and Communication Engineering Shanxi Electronic Science and Technology Institute Linfen041000 China School of Data Science and Technology North University of China Shan Xi Taiyuan030051 China

The precise classification recognition of dangerous driving behaviors can effectively reduce traffic accidents and improve road safety. To address the challenges of complex and dynamic traffic environments where driving behaviors can vary significantly’ an innovative method for classification recognizing for dangerous driving behaviors has been developed’ utilizing an enhanced k-means clustering algorithm. Wavelet decomposition is aPPlied to denoise the image data of driving behaviors. The refined data is then effectively categorized using the improved k-means clustering technique to discern distinct driving actions. Convolutional neural networks are employed to extract and classify critical action areas’ enabling precise identification of hazardous driving behaviors. Test results demonstrate that this designed method achieves a maximum classification recognition rate of 98% for dangerous driving behaviors’ with shorter recognition processing time. © 2024, Aracne Editrice. All rights reserved.

关键词： K-means clustering

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Temporal Convolutional Network for Speech Bandwidth Extension

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China communications 2023年第11期20卷 142-150页

作者： Chundong Xu Cheng Zhu Xianpeng Ling Dongwen Ying School of Information Engineering Jiangxi University of Science and TechnologyJiangxi 341000China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100049China

In the field of speech bandwidth exten-sion,it is difficult to achieve high speech quality based on the shallow statistical model *** the application of deep learning has greatly improved the extended speech quality,the high model complex-ity makes it infeasible to run on the *** order to tackle these issues,this paper proposes an end-to-end speech bandwidth extension method based on a temporal convolutional neural network,which greatly reduces the complexity of the *** addition,a new time-frequency loss function is designed to en-able narrowband speech to acquire a more accurate wideband mapping in the time domain and the fre-quency *** experimental results show that the reconstructed wideband speech generated by the proposed method is superior to the traditional heuris-tic rule based approaches and the conventional neu-ral network methods for both subjective and objective evaluation.

关键词： speech bandwidth extension temporal convolutional networks time-frequency loss

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HUID:DBN-Based Fingerprint Localization and Tracking System with Hybrid UWB and IMU

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China communications 2023年第2期20卷 139-154页

作者： Junchang Sun Rongyan Gu Shiyin Li Shuai Ma Hongmei Wang Zongyan Li Weizhou Feng School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Peng Cheng Laboratory Shenzhen 518055China School of Information and Communications Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

High-precision localization technology is attracting widespread attention in harsh indoor *** this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based on a deep belief network(DBN).In this system,we propose using coefficients as fingerprints to combine the ultra-wideband(UWB)and inertial measurement unit(IMU)estimation linearly,termed as a HUID *** particular,the fingerprints are trained by a DBN and estimated by a radial basis function(RBF).However,UWB-based estimation via a trilateral method is severely affected by the non-line-of-sight(NLoS)problem,which limits the localization *** tackle this problem,we adopt the random forest classifier to identify line-of-sight(LoS)and NLoS ***,we adopt the random forest regressor to mitigate ranging errors based on the identification results for improving UWB localization *** experimental results show that the mean square error(MSE)of the localization error for the proposed HUID system reduces by 12.96%,50.16%,and 64.92%compared with that of the existing extended Kalman filter(EKF),single UWB,and single IMU estimation methods,respectively.

关键词： Ultra-wideband(UWB) inertial measurement unit(IMU) fingerprints positioning NLoS identification estimated errors mitigation deep belief network(DBN) radial basis function(RBF)

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Activation Distance and Capacity Analysis for Ambient Backscatter communications with Sensitivity Constraint and Beamforming

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China communications 2024年第11期21卷 257-266页

作者： Mu Yunping Fan Dian Wang Gongpu Xu Yongjun Kuang Lei Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education School of Computer and Information TechnologyBeijing Jiaotong UniversityBeijing 100044China China Academy of Information and Communications Technology Beijing 100191China School of Communication and Information Engineering Chongqing University of Posts and TelemcommunicationsChongqing 400065China Shanghai Key Laboratory of Multidimensional Information Processing Engineering Center of SHMEC for Space Information and GNSSSchool of Information Science and TechnologyEast China Normal UniversityShanghai 200241China

Circuit sensitivity of sensors or tags without battery is one practical constraint for ambient backscatter communication *** letter considers using beamforming to reduce the sensitivity constraint and evaluates the corresponding performance in terms of the tag activation distance and the system ***,we derive the activation probabilities of the tag in the case of single-antenna and multi-antenna ***,we obtain the capacity expressions for the ambient backscatter communication system with beamforming and illustrate the power allocation that maximizes the system capacity when the tag is ***,simulation results are provided to corroborate our proposed studies.

关键词： activation distance ambient backscatter communications beamforming channel capacity power allocation sensitivity

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Deep Reinforcement Learning Based Joint Cooperation Clustering and Downlink Power control for Cell-Free Massive MIMO

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China communications 2024年第11期21卷 1-14页

作者： Du Mingjun Sun Xinghua Zhang Yue Wang Junyuan Liu Pei School of Electronics and Communication Engineering Sun Yat-sen UniversityShenzhen 518107China Department of Electronic and Information Engineering Shantou UniversityShantou 515063China College of Electronic and Information Engineering Tongji UniversityShanghai 201804China School of Information Engineering Wuhan University of TechnologyWuhan 430070China Zhongshan Institute of Advanced Engineering Technology of Wuhan University of Technology Zhongshan 528437China

In recent times,various power control and clustering approaches have been proposed to enhance overall performance for cell-free massive multipleinput multiple-output(CF-mMIMO)*** the emergence of deep reinforcement learning(DRL),significant progress has been made in the field of network optimization as DRL holds great promise for improving network performance and *** this work,our focus delves into the intricate challenge of joint cooperation clustering and downlink power control within CF-mMIMO *** the potent deep deterministic policy gradient(DDPG)algorithm,our objective is to maximize the proportional fairness(PF)for user rates,thereby aiming to achieve optimal network performance and resource ***,we harness the concept of“divide and conquer”strategy,introducing two innovative methods termed alternating DDPG(A-DDPG)and hierarchical DDPG(H-DDPG).These approaches aim to decompose the intricate joint optimization problem into more manageable sub-problems,thereby facilitating a more efficient resolution *** findings unequivo-cally showcase the superior efficacy of our proposed DDPG approach over the baseline schemes in both clustering and downlink power ***,the A-DDPG and H-DDPG obtain higher performance gain than DDPG with lower computational complexity.

关键词： cell-free massive MIMO clustering deep reinforcement learning power control

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DSCCNet for high-quality 4K computer-generated holograms

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Optics Express 2025年第6期33卷 13733-13747页

作者： Xu, Zhenqi Leng, Junmin Dai, Ping Wang, Chao Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing100101 China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100101 China School of Information and Communications Engineering Beijing Information Science and Technology University Beijing100101 China

With the increasing demand for high-quality 3D holographic reconstruction, visual clarity and accuracy remain significant challenges in various imaging applications. Current methods struggle for higher image resolution and to resolve such issues as detail loss and checkerboard artifacts. To address these challenges, we propose the model Depthwise Separable Complex-valued Convolutional Network (DSCCNet) for phase-only computer-generated holography (CGH). This deep learning framework integrates complex-valued convolutions with depthwise separable convolutions to enhance reconstruction precision and improve model training efficiency. Additionally, the diffuser is employed to reduce checkerboard artifacts in defocused parts of 3D CGH. Experimental results demonstrate that DSCCNet can obtain 4K images reconstructed with more intricate details. The reconstruction quality of both 2D and 3D layered objects is enhanced. Validation on 100 images from the DIV2K dataset shows an average PSNR above 37 dB and an average SSIM above 0.95. The proposed model provides an effective solution for high-quality CGH applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Computer generated holography

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Using ontology and rules to retrieve the semantics of disaster remote sensing data

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Journal of Systems engineering and Electronics 2024年第5期35卷 1211-1218页

作者： DONG Yumin LI Ziyang LI Xuesong LI Xiaohui Key Laboratory of Quantitative Remote Sensing Information Technology Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100049China

Remote sensing data plays an important role in natural disaster ***,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster field retrieve remote sensing *** improve this problem,this paper proposes an ontology and rule based retrieval(ORR)method to retrieve disaster remote sensing data,and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge,on this basis,and realizes the task suitability reasoning of earthquake disaster remote sensing data,mining the semantic relationship between remote sensing metadata and *** prototype system is built according to the ORR method,which is compared with the traditional method,using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.

关键词： remote sensing data disaster ontology semantic reasoning

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Genetic Algorithm-Based Robot Path Planning with the Extraction of Topological Map 13

Genetic Algorithm-Based Robot Path Planning with the Extract...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Liu, Zhen Xu, Jinglue Iba, Hitoshi Graduate School of Information Science and Technology The University of Tokyo Department of Information and Communication Engineering Tokyo Japan

ISBN: (纸本)9798350308365

Genetic algorithm (GA) is a common approach for multi-objective path planning. However, conventional GA performs poorly on large-scale complex maps due to the lack of an efficient initialization method and the infeasible solutions generated during the GA search. In this paper, first, we propose an innovative initialization method. The proposed method extracts the division points of the map and constructs a topological map, allowing the initialization of feasible paths based on the fitness function. Second, we calculate the estimated fitness value of each path in the topological map. Paths with low estimated fitness values will not be initialized, reducing the search space. In addition, we improve the crossover of GA, preventing the generation of infeasible paths by utilizing the topological map. The proposed method is compared against Theta∗, A ∗(adjusted to consider smoothness), and conventional genetic algorithms on small and large-scale maps. The proposed method has outperformed previous methods regarding fitness value, reducing the runtime by more than 37% on large-scale maps. © 2024 IEEE.

关键词： genetic algorithm path planning topological map

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A Low-Cost Robotic Assembly Method for Large Planar Workpieces Using Laser Displacement Sensors and Monocular Vision

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第17期49卷 155-172页

作者： Cao, Xiaobing Xu, Yicen Yao, Yonghong Chen, Sheng School of Control Technology Wuxi Institute of Technology Wuxi Jiangsu214121 China School of Intelligent Equipment and Automotive Engineering Wuxi Institute of Commerce Wuxi Jiangsu214153 China School of Communication and Electronic Engineering East China Normal University Shanghai200062 China

To address the challenges associated with large planar workpieces, such as the side window glass of a train, this paper proposes a practical, intelligent robotic assembly method that utilizes laser displacement sensors (LDSs) and monocular vision. The laser point cloud data is fitted to the equation of the plane of the side window optimally, allowing for the calculation of its plane coefficients and unit normal vector (UNV) using the Lagrange multiplier method. The robot's end flange is adjusted to ensure the camera imaging plane is along with the window plane at a specified distance. Monocular vision is employed to capture the pose features of the upper right corner of the window, facilitating a compensation method for precise assembly. The experimental results show that the robot achieved a positioning accuracy of less than 0.5mm and an orientation accuracy within 1 degree, confirming the effectiveness of the proposed method. In the experiment, the maximum displacement deviation in the X direction is about ± 0.4mm, the maximum offset in the Y and Z directions is about ± 0.3mm, the maximum rotation deviation in the X axis is about 0.6 °, and the minimum rotation deviation in the Y axis is about 0.8 °. All deviations meet the requirements of ± 1 ° attitude correction and ± 0.5mm displacement accuracy, and have good reliability. This method solves the practical problem of assembling large planar workpieces with integrated LDS and monocular vision. This technology involves using laser point cloud data to fit the precise plane equation of the window, determining alignment parameters through Lagrange multiplier method, and adjusting the posture of the end flange of the robot. Monocular vision further assists in extracting positional features, achieving precise real-time posture correction and alignment. This system proposes an effective and low-cost automation that reduces manual intervention and alleviates typical problems of remote processing of large workpieces. © 20

关键词： Lagrange multipliers

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Policy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal control

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1060-1062页

作者： Hao Zhang Yan Li Zhuping Wang Yi Ding Huaicheng Yan the Department of Control Science and Engineering Tongji UniversityShanghai 200092China the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education School of Information Science and EngineeringEast China University of Science and TechnologyShanghai 200237China

Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is... 详细信息

关键词： policy gradient Optimal

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