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11th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2023 - Proceedings

作者： Xu, Xiaochun Feng, Huibin Wu, Qihang Guo, Ente Wang, Xinxin Minjiang University College of Computer and Control Engineering Fuzhou350108 China Minjiang University International Digital Economy College Fuzhou350108 China

ISBN: (纸本)9798350326277

Boundary effect, as an inherent drawback of discriminative correlation filter (DCF) trackers, cannot be handled well in most existing studies. This paper proposes an adaptive enhanced windowed correlation filter tracker (AEWCF), which can alleviate boundary effect adaptively and capture more reliable target information effectively. Firstly, a target enhanced likelihood map is introduced to extract reliable target information from searching window. Then, this paper further proposes an adaptive parted searching window including two sub-windows: the object region window depended on object likelihood maximization strategy and the background window generated by background suppression scheme. The extensive evaluation on OTB2015 benchmarks demonstrate that the AWCF tracker performs favorably against some popular trackers and keeps real-time speed. © 2023 IEEE.

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Optimized Algebraic Decoding Algorithm for (47, 24, 11) QR Code 5

Optimized Algebraic Decoding Algorithm for (47, 24, 11) QR C...

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5th International Conference on Information Communication and Signal Processing, ICICSP 2022

作者： Luo, Chunlan Zhu, Xiaoxia College of Computer and Control Engineering Minjiang University Fujian Fuzhou China

ISBN: (纸本)9781665485890

A fast decoding algorithm scheme is proposed for the quadratic residue code with code length of 47 and large error-correcting capacity of 5 errors in this paper, called optimized algebraic decoding algorithm (OADA). The main contributions of this article are to deduce a method to quickly compute the related unknown syndrome of (47,24,11) QR code and a simpler discriminant condition to detect whether four errors occurred in the received word. The decoding algorithm scheme needs lower memory requirement compared with the algorithm based on the full hard decision algebraic decoding algorithm. For exhaustive simulation test of all the error patterns shows that the proposed algorithm of (47, 24, 11) QR code improves the decoding performance and decoding efficiency. © 2022 IEEE.

关键词： Decoding

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A Completed Gaussian Extended Binary Pattern for Texture Image Classification 2

A Completed Gaussian Extended Binary Pattern for Texture Ima...

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2nd International Conference on Signal Processing, computer Networks and Communications, SPCNC 2023

作者： Xu, Xiaochun Lin, Weizheng Chen, Dingrong Su, Nanling Tang, Leinuo Cai, Changxu College of Computer and Control Engineering Minjiang University Fuzhou350108 China International Digital Economy College Minjiang University Fuzhou350108 China

ISBN: (纸本)9798400716430

Texture image classification is a fundamental and challenging visual task and has wide range of applications. Binary pattern methods play an important role in texture feature extraction due to its ease of implementation and promising performance. To extract completed texture feature representation and improve the classification performance, this paper proposes a completed gaussian extend binary pattern for texture image classification. First, instead of the original pixel value, this paper uses the mean of local range to encode the binary pattern. Second, this paper introduces a novel gaussian sign pattern to fully represent the macro texture structure. Third, to achieve completed texture feature description, this paper presents a completed gaussian extended binary pattern, which combines the novel gaussian sign pattern, the local sign and magnitude pattern extracted from mean-processing texture image. To validate the effectiveness of the proposed completed gaussian extend binary pattern, experimental evaluations are conducted on three test subsets from Outex database. The evaluation results show that the proposed completed gaussian extended binary pattern achieves the state-pf-the-art classification performance. © 2023 ACM.

关键词： Feature extraction

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Reinforcement learning-based unknown reference tracking control of HMASs with nonidentical communication delays

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Science China(Information Sciences) 2023年第7期66卷 46-57页

作者： Yong XU Zheng-Guang WU Wei-Wei CHE Deyuan MENG School of Automation Beijing Institute of Technology Institute of Cyber-Systems and Control Zhejiang University College of Mathematics and Computer Science Zhejiang Normal University Department of Automation Qingdao University School of Automation Science and Electrical Engineering Beihang University(BUAA)

This paper focuses on the optimal output synchronization control problem of heterogeneous multiagent systems(HMASs) subject to nonidentical communication delays by a reinforcement learning *** with existing studies assuming that the precise model of the leader is globally or distributively accessible to all or some of the followers, the leader's precise dynamical model is entirely inaccessible to all the followers in this paper. A data-based learning algorithm is first proposed to reconstruct the leader's unknown system matrix online. A distributed predictor subject to communication delays is further devised to estimate the leader's state, where interaction delays are allowed to be nonidentical. Then, a learning-based local controller, together with a discounted performance function, is projected to reach the optimal output synchronization. Bellman equations and game algebraic Riccati equations are constructed to learn the optimal solution by developing a model-based reinforcement learning(RL) algorithm online without solving regulator equations, which is followed by a model-free off-policy RL algorithm to relax the requirement of all agents' dynamics faced by the model-based RL algorithm. The optimal tracking control of HMASs subject to unknown leader dynamics and communication delays is shown to be solvable under the proposed RL algorithms. Finally, the effectiveness of theoretical analysis is verified by numerical simulations.

关键词： heterogeneous multiagent systems HMAS reinforcement learning RL optimal output synchronization communication delays

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An Automatic Object Attention Likelihood Map Correlation Filter for Visual Tracking 11

An Automatic Object Attention Likelihood Map Correlation Fil...

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11th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2023 - Proceedings

作者： Tang, Leinuo Xu, Xiaochun Wang, Xin Feng, Huibin Lin, Nixuan Minjiang University International Digital Economy College Fuzhou350108 China Minjiang University College of Computer and Control Engineering Fuzhou350108 China

ISBN: (纸本)9798350326277

Discriminative correlation filter-based trackers have achieved excellent performance. However, they are still suffered from the inherent boundary effect. To alleviate it, this paper proposes an automatic object attention likelihood map correlation filter. Specifically, an automatic object attention searching window is developed to highlight the object more precisely and suppress the background more appropriately, which divides the searching area into three regions and applies different object attention strategies on each area. Furthermore, combining it with the spatially regularized discriminative correlation filter, we propose the automatic object attention likelihood map correlation filter tracker. It further alleviates the boundary effect and adaptively generates a more precise tracking model frame by frame. The experimental evaluations on the popular OT2015 benchmark demonstrate that our proposed tracker gains outstanding tracking performance and offers a satisfying robustness to complex tracking scenarios. © 2023 IEEE.

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An efficient and high-performance WSNs restoration algorithm for fault nodes based on FT in data aggregation scheduling

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International Journal of Cognitive Computing in engineering 2025年 6卷 508-515页

作者： Li, Cheng Zhang, Guoyin College of Computer Science and Technology Harbin Engineering University Heilongjiang Harbin150001 China College of Computer and Control Engineering Qiqihar University Heilongjiang Qiqihar161006 China

In wireless sensor networks(WSNs), data aggregation effectively reduces network traffic, thereby reducing energy consumption and improving network life cycle. Nevertheless, in the process of data aggregation scheduling, if there are fault nodes, the data quality collected by the whole network will decline, and the network performance will decrease, even posing a threat to network security or causing network paralysis. Thus, an efficient and high-performance WSNs restoration algorithm is proposed based on fat tree(FT), which is referred to as the EPRA-FT algorithm. And our goal is to improve the universality, efficiency, and performance retention of the algorithm. Previously, we have conducted a range of the relevant researches on performance improvement of WSNs aggregation scheduling by adopting FT structure, and some successful results have been obtained. On the basis of these results, for the EPRA-FT algorithm, first and foremost, the relationship among nodes is comprehensively recorded in FT construction process. Then, fault nodes are shielded by deleting the known nodes in aggregation tree. Finally, the local reconfiguration of aggregation tree is completed quickly and efficiently. Meanwhile, the aggregation scheduling performance of the original network is maintained to the maximum extent. The feasibility and superiority of our proposed EPRA-FT algorithm are proved by simulation experiments. © 2025

关键词： Wireless sensor networks

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Performance analysis of UAV-based mixed underwater PLC-RF systems

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Digital Communications and Networks 2024年第5期10卷 1332-1340页

作者： Shenghai Chen Liang Yang Xianfu Lei College of Computer Science and Electronic Engineering Hunan UniversityChangsha410082China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua418000China School of Information Science and Technology Southwest Jiaotong UniversityChengdu610031China

In this study,we analyzed the performance of an Unmanned Aerial Vehicle(UAV)-based mixed Underwater Power Line Communication-Radio Frequency(UPLC-RF)*** this network,a buoy located at the sea is used as a relay to transmit signals from the underwater signal source to the UAV through the PLC *** assume that the UPLC channel obeys a log-normal distribution and that the RF link follows the Rician *** this model,we obtained the closed-form expressions for the Outage Probability(OP),Average Bit-error-rate(ABER),and Average Channel Capacity(ACC).In addition,the asymptotic analysis of the OP and ABER was performed,and an upper bound for the average capacity was ***,the analytical results were verified by Monte Carlo simulation thereby demonstrating the effect of impulse noise and the altitude of the UAV on network performance.

关键词： ABER Average bit-error-rate ACC Average channel capacity OP Outage probability UAV Unmanned aerial vehicle UPLC Underwater power line communication

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Optimization of Magnetic Couplers in Wireless Charging Systems Using the Surrogate Model

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Li, Zhenjie Li, Xianzhen Yuan, Dechun Zhang, Jiawei Liu, Yiqi Northeast Forestry University College of Computer and Control Engineering Harbin150040 China

This article proposes a general and efficient surrogate model-based parameter optimization method, consisting of the Taguchi method, finite element method (FEM) simulation, genetic algorithm-backpropagation (GA-BP) neural network, and grid search, to optimize various magnetic coupler with multiple design objectives in wireless charging systems (WCS). First, the WCS with hub-type multiple circular coil coupler (HMTC) is used as an example to validate the necessity of parameter optimization for the magnetic coupler. Then, the HMTC's structure and principles are analyzed. Three design objectives with function expressions are used as examples for designing an HMTC: the rated mutual inductance, high misalignment tolerance, and lightweight receiver. Second, a detailed workflow of the proposed method is analyzed, especially the basic working principles of the Taguchi method and GA-BP neural network-based surrogate model. Third, the HMTC optimization process and the proposed method's main parameter determination are analyzed. Then, simulation results verify the proposed method's feasibility on HMTC and two other magnetic couplers. Numerical results prove that the proposed method has higher optimization efficiency and accuracy. Finally, a prototype is built. Experimental results confirm that the rated mutual inductance is 20.2 μH, and its fluctuation within ±5% is circular (radius is 34% of the transmitter diameter). © 2013 IEEE.

关键词： Inductive power transmission

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Kernel-Guided Texture-Aware Blind Super-Resolution via Uncertainty Learning 13

Kernel-Guided Texture-Aware Blind Super-Resolution via Uncer...

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13th International Conference on Information Technology in Medicine and Education, ITME 2023

作者： Zhao, Tingting Li, Zuoyong Quan, Li Zeng, Kun Teng, Shenghua College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China College of Computer Science and Big Data Fuzhou University Fuzhou350121 China

ISBN: (纸本)9798350319156

The accuracy of kernel estimation is critical to the performance of blind super-resolution (SR). Traditional kernel estimation methods usually use L1 or L2 loss function to minimize the difference between the estimated kernel and the ground-truth kernel. This tends to make the estimated kernel converge towards the average of all possible kernels, deviating from the ground-truth kernel. To improve the performance of kernel estimation, this paper proposes an uncertainty loss for training a kernel estimation network, focusing on regions with high uncertainty (variance) in the kernel. In addition, a texture-aware SR network is proposed that utilizes the Gumbel Softmax trick to pay more attention to the complex regions of the image texture, thus improving the SR performance. Extensive experiments on synthetic datasets show that our approach achieves promising performance. © 2023 IEEE.

关键词： Textures

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GITANet: Group Interactive Threshold-based Attention Network for Hyperspectral Image Classification

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IEEE Transactions on Multimedia 2025年 27卷 3571-3584页

作者： Duan, Yule Chen, Chuang Fu, Maixia Gong, Xiuwen Niu, Yingying Luo, Fulin The University of Sydney Faculty of Engineering NSW2006 Australia Henan University of Technology Key Laboratory of Grain Information Processing and Control Ministry of Education Zhengzhou450001 China Henan University of Technology Key Laboratory of Grain Photoelectric Detection and Control Zhengzhou450001 China Chongqing University College of Computer Science Chongqing400044 China

Group convolution networks have shown great potential in hyperspectral image (HSI) classification because of their ability to divide total spectral bands into multiple groups and focus on fine discrimination within different spectral ranges. Most group convolution networks process parallel spectral groups independently;however, they neglect the important relevance of nearby spectral ranges. Moreover, the feature maps from different spectral groups are not considered for recalibration in the existing attention. To address these issues, we propose a novel group interactive threshold attention network (GITANet). In the network, a stratified-split-concatenation strategy, which not only splits all bands into multiple groups for intragroup convolution but also propagates the intergroup information via the stratified concatenation operation between different groups, is designed for bandwise group convolution. Relying on the high dependencies among nearby spectra, the cross-group interactive attention block is designed to encourage significant spectral features. Subsequently, from different spectral ranges, a learnable threshold generation block is built to estimate the information validity of each pixel. On the basis of this threshold, soft threshold spatial attention is developed in the bandwise encoderdecoder architecture, which emphasizes high-value spatial areas during the fusion of group convolutional features. Therefore, complementary and discriminative spectral-spatial features are obtained to improve the performance of HSI classification. The experimental results on three HSI datasets illustrate that GITANet is superior to several state-of-the-art networks. © 1999-2012 IEEE.

关键词： Convolution

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