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Tracking control for nonlinear multi-agent systems: a first-order DPG framework with initial admissible control policy method

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NONLINEAR DYNAMICS 2025年第14期113卷 18177-18194页

作者： Rao, Jun Wang, Jingcheng Xu, Jiahui Zhong, Yanjiu Shanghai Jiao Tong Univ Dept Automat Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

As a primary method to solve the optimal tracking control problem for nonlinear multi-agent systems, policy gradient approach with traditional multi-agent actor-critic network structures suffers from lengthy training time and stability. In this article, we propose a novel first-order deterministic policy gradient framework with an initial admissible control policy method (I-FDPG). An additional first-order critic network and its target network are introduced to estimate the partial derivatives of the value function with respect to the tracking error. Updated by the estimation error of the values and the policy gradient alternately, the iterative process of control policy is improved. Moreover, when determining the initial control policy, a dynamic iterative termination criterion is proposed since the fixed iterative termination criterion is often unsuitable for each agent. The boundedness, convergence and optimality of the I-FDPG algorithm are proven. Finally, the effectiveness of the proposed algorithm is validated through a two-dimensional affine nonlinear multi-agent system.

关键词： Tracking control Nonlinear multi-agent systems Policy gradient Initial control policy

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A Dual-Mode Coupling MMW Antenna With Dual Polarizations and Wide Scanning Angles

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2025年第3期24卷 542-546页

作者： Pan, Long Wang, Rui Luo, Yong Shanghai Univ Sch Commun & Informat Engn Shanghai Key Lab Chips & Syst Intelligent Connecte Shanghai 201900 Peoples R China

Millimete-wave (MMW) communication and sensing systems suffer from the challenge of realizing dual-polarized phased array antenna with large beam-scanning angles, due to the array unit can hardly having the radiation pattern with wide 3 dB beamwidth in both orthogonal planes (one is the beam-scanning plane). In this letter, we propose a dual-mode coupling radiation mechanism to integrate a monopole mode and a patch mode for obtaining 3 dB beamwidth larger than 120 degrees in both two orthogonal planes. Hence, the array cascaded from the antenna unit can realize a wide beam scanning of -60 degrees similar to+60 degrees within gain degradation of less than 3 dB in both +/- 45 degrees polarizations. Based on this principle, a +/- 45 degrees dual-polarized antenna unit is designed, and a prototype of a 1 x 8 +/- 45 degrees dual-polarized phased array is fabricated. Experiments demonstrate that the MMW array operating in 25.5 GHz to 28 GHz (active |S-11|< -10 dB) can scan from -60 degrees to +60 degrees with gain fluctuations less than 3 dB. The proposed MMW antenna can be applied to B5G/6G MMW communications and sensing.

关键词： Phased arrays Antenna radiation patterns Couplings Antennas Substrates Slot antennas Bandwidth Sensors Patch antennas Gain +/- 45 degrees dual polarizations dual-mode coupling radiation large beam-scanning angles millimeter-wave (MMW) antenna

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Subdivision of Adjacent Areas for 3D Point Cloud Semantic Segmentation

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SIGNAL IMAGE AND VIDEO procESSING 2025年第1期19卷 1-13页

作者： Xu, Haixia Hu, Kaiyu Xu, Yuting Zhu, Jiang Xiangtan Univ Sch Automat & Elect Informat Key Lab Intelligent Comp & Informat Proc Minist Educ Xiangtan 411100 Peoples R China

In 3D point cloud semantic segmentation, much of the previous research has focused on aggregating the fine-grained geometric structures of local regions, overlooking the long-term features. However, global long-term contextual dependencies play a role as important as local features aggregation. This paper proposes a Subdivision of Adjacent Areas (SAA) module, which efficiently mines more informative features to enrich global long-term contextual dependencies. SAA is constructed by the CoVariance-Enhanced Channel Attention (CECA) and the PseudoNL Spatial Attention (PSA). The former learns the interdependence among channels via second-order statistics for each feature channel, while the latter efficiently captures the positional correlation among points in the entire space via a pseudo feature map. The proposed SAA, a plug-and-play, end-to-end trainable module, can be integrated into existing segmentation networks. Extensive experiments on S3DIS and ScanNet datasets demonstrate that networks integrated with our SAA improve mIoU performance. It verifies that SAA is beneficial for 3D point cloud segmentation networks in achieving excellent performance.

关键词： Semantic segmentation 3D point cloud Global attention Deep learning

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GazeViT: A gaze-guided hybrid attention vision transformer for cross-view matching of street-to-aerial images

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PATTERN RECOGNITION LETTERS 2025年 191卷 80-88页

作者： Hu, Yidong Tong, Li Gao, Yuanlong Zeng, Ying Yan, Bin Li, Zhongrui PLA Cyberspace Force Informat Engn Univ Henan Key Lab Imaging & Intelligent Proc Zhengzhou Peoples R China

The goal of cross-view matching between street and aerial images is to retrieve aerial-view images that correspond to a given street-view image from a database of GPS-tagged aerial images. This task relies on image crossview matching technology, focusing on the extraction and alignment of features representing the same location in both image types. The significant differences in perspective and appearance between street-view images and aerial-view images present a challenge. Aerial-view images cover a broader area, while street-view images focus on specific locations, creating information asymmetry that complicates the matching process. To tackle these challenges, this paper proposes a gaze-guided hybrid attention Vision Transformer, which uses gaze information to guide the model to focus on and align task-related features. Furthermore, inspired by the human visual cognitive process of "focus and zoom," we develop a hybrid attention module alongside an image adaptive cropping and resolution enhancement module. The hybrid attention module utilizes gaze information to guide the model to focus on relevant regions, while the image adaptive cropping strategy uses gaze information to guide the model to eliminate irrelevant regions. Techniques for improving image resolution allow for the magnification of important regions, thereby aiding the extraction of fine-grained features. We evaluate the model's performance on benchmark datasets and conduct ablation study experiments to assess the contributions of each module. Experimental results show that the method achieves a top-1 accuracy of 75.56 % on the CVACT dataset, representing state-of-the-art performance. This study provides valuable insights into incorporating human experience into computational models, particularly through gaze-guided learning of visual task networks to enhance model performance.

关键词： Street-to-aerial images Cross-view matching Hybrid attention Eye tracking Machine vision and image processing

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Dual stream fusion module integrating 2D and 3D for 3D semi-supervised medical image segmentation

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SIGNAL IMAGE AND VIDEO procESSING 2025年第4期19卷 1-11页

作者： He, Zhiquan Ouyang, Yating Wen, Yang Shenzhen Univ Guangdong Prov Key Lab Intelligent Informat Proc Nanhai Blvd Shenzhen 518060 Peoples R China

Semi-supervised learning has proven effective in the challenging field of 3D medical image segmentation. However, existing methods typically focus solely on utilizing 3D features, which limits their ability to capture local differences effectively. To address this limitation, we propose a Dual Stream Fusion Model (DSFM) that fuses both 3D and 2D features, enabling the model to capture both global and local information. The model consists of a Cross-Dimensional Attention Fusion Module (CDAFM) and a Self-Adaptive Fusion Module (SAFM). The CDAFM integrates 3D and 2D features using an attention mechanism, while the SAFM merges the segmentation results from both modalities through adaptive weighting. Together, these modules enhance the model's ability to focus on local differences while simultaneously learning global features. Specifically, the 3D decoder receives fused features from both the 3D and 2D encoders, and the final segmentation result is produced by combining the outputs of both the 3D and 2D decoders. Furthermore, we introduce an alignment loss to enforce consistency between the 3D and 2D segmentation sub-networks through regularization. Comprehensive experiments on four publicly available 3D medical datasets demonstrate the effectiveness of our approach. Notably, on the BRaTS19 dataset, which contains only 20% annotated images, we observe a 2.83% improvement in the Jaccard index.

关键词： Dual stream fusion Joint 3D and 2D learning Semi-supervised learning Medical image segmentation

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Pseudolite Self-Interference Cancellation Without Additional GNSS Signal Distortion

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IEEE ACCESS 2025年 13卷 55927-55938页

作者： Gao, Lichao He, Jin Wu, Yuanxin Yu, Wenxian Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Key Lab Intelligent Sensing & Recognit Shanghai 200240 Peoples R China

The goal of this paper is to solve the low-orbit pseudolite self-interference problem. The low-orbit pseudolite navigation signals will interference satellite navigation as they broadcast at the same frequency and same time. However, the low-orbit pseudolite also needs satellite navigation to get continuous and effective high-precision positioning. So, while effectively filtering the self-interference, the GNSS navigation signals need low distortion. In this paper, we propose an anti-self-interference method which ensures that GNSS navigation signals are not distorted. Specifically, the method uses the known characteristics of self-interference signals to establish an optimization problem. By solving this problem, self-interference filtering can be achieved without estimating the direction of satellite navigation signal and without the assistance of the receiver channel amplitude-frequency and phase-frequency characteristics. The simulation test results show that the algorithm can filter self-interference without additional distortion of the satellite navigation signals. The application test results show that, the algorithm can filter self-interference with high-precision carrier observation of the satellite navigation signal which statistical standard deviation is only 0.01 times of the carrier wavelength. The method could help in achieving high-precision satellite navigation and positioning of pseudolite terminals and providing high-precision position information for low-orbit pseudolites.

关键词： Satellite broadcasting Satellites Interference cancellation Global navigation satellite system Receiving antennas Aircraft navigation Accuracy Filtering algorithms Calibration Full-duplex system Pseudolite navigation self-interference cancellation GNSS zero-distortion low-orbit

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Exploring Cultural and Intergenerational Dynamics in Voice Assistant Design for Chinese Older Adults

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procEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT 2025年第1期9卷 1-18页

作者： Qian, Zhigu Fu, Jiaojiao Zhou, Yangfan Fudan Univ Sch Comp Sci Shanghai Peoples R China Shanghai Key Lab Intelligent Informat Proc Shanghai Peoples R China East China Univ Sci & Technol Sch Informat Sci & Engn Shanghai Peoples R China

In this study, we examined voice assistant (VA) use among Chinese older adults through interviews with 12 older adults and 6 of their adult children, as well as observations of VA use in solo and family settings. Our findings reveal that older adults are motivated to use VA for social interaction but encounter barriers due to limited cultural and linguistic customization, such as difficulty understanding regional dialects. Additionally, adult children play a dual role, providing necessary support while sometimes limiting independent use through overprotective tendencies. These results highlight the importance of designing VA with culturally responsive features and adaptable language models that consider the unique linguistic and social needs of older Chinese adults. This study contributes to the development of VA that balances autonomy and family support, enriching the technology's effectiveness for older adults in China and potentially in other similar cultural contexts.

关键词： Human-centered computing Empirical studies in HCI

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Dual-Stream Image Sharing Chain Detection via Dynamic information Compensation

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IEEE SIGNAL procESSING LETTERS 2025年 32卷 1311-1315页

作者： Su, Xinyi Li, Yuanman Zheng, Yulong Li, Xia Shenzhen Univ Coll Elect & Informat Engn Guangdong Prov Key Lab Intelligent Informat Proc Shenzhen 518060 Peoples R China

Image Sharing Chain Detection (ISCD) aims to reconstruct the complete trajectory of an image's dissemination across social platforms and is an important task in multimedia forensics. Current methods using DCT histograms are insufficient in uncovering platform compression traces and exhibit limitations in detecting weak trace platforms. In this letter, we propose an innovative dual-stream ISCD framework via dynamic information compensation. This framework integrates features from both the frequency domain and the residual domain to extract compression characteristics. Unlike existing methods, we employ binary stereo DCT in the frequency domain to focus on the spatiality of compression operations. Additionally, we design a dynamic information compensation mechanism to enhance platform traces by storing compensation fingerprints of the sharing chains. Furthermore, we develop a new dataset, F-4OSN-SC, encompassing 4 platforms to simulate more realistic social networking scenarios. Experimental results demonstrate that our model outperforms existing methods across multiple datasets.

关键词： Discrete cosine transforms Feature extraction Image coding Fingerprint recognition Noise Frequency-domain analysis Training Histograms Data mining Social networking (online) Image forensics image sharing chain detection dynamic information compensation online social platforms

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XPtychoSR: a self-supervised super-resolution framework for X-ray ptychography

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APPLIED OPTICS 2025年第11期64卷 2872-2879页

作者： Liu, Mengnan Han, Yu Xi, Xiaoqi Zhang, Liyang Zhong, Qi Zhu, Linlin Li, Lei Yan, Bin Informat Engn Univ Henan Key Lab Imaging & Intelligent Proc Zhengzhou 450001 Peoples R China

Ptychography has been extensively used for nanoscale imaging of catalysts, cells, and chips. The interpolationbased magnification is no longer adequate. A clearer imaging quality is expected for observing fine structures in the reconstructed images. While deep-learning-driven super-resolution (SR) techniques have been successful, pretrained or supervised strategies are still challenging in X-ray ptychography experiments as generalization and large training datasets need to be considered. A self-supervised SR method named XPtychoSR is proposed to further discern the reconstruction details in the large field of view (FOV) X-ray ptychography data. XPtychoSR generates clear SR results based on only one input, without pre-training and matched (or unmatched) datasets. XPtychoSR extracts the content prior and the edge prior of the input, which is fused with the implicit image prior constructed by a U-shaped net to enhance detail expressiveness in the SR image. A physics diffraction model (PDM)-based reconstruction method is used to guide the network to self-supervised learning, resulting in an SR image with superior detail. The simulation and soft X-ray ptychography experiment show that XPtychoSR has better detail resolution ability than the existing advanced SR technologies. Ablation experiments demonstrate the effectiveness of the components and framework in XPtychoSR. XPtychoSR adapts to the need for SR imaging in the large FOV and detailed viewing in the region of interest (ROI). The method avoids additional adjustments and costs in hardware. These improvements further extend the application of X-ray ptychography. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Imaging systems Imaging techniques Machine vision Optical imaging Wavelet transforms Zone plates

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Event-triggered distributed model predictive control for PWA systems

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2025年第2期35卷 435-451页

作者： Ma, Aoyun Li, Dewei Xi, Yugeng Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai Peoples R China Shanghai Engn Res Ctr Intelligent Control & Manage Shanghai Peoples R China

The online computational burden and control performance are two main issues in implementing distributed model predictive control for piecewise affine systems. In the previous research, many methods have been proposed to solve these issues, such as a one-step distributed model predictive control method that was proposed to reduce the heavy online computational burden. However, its control performance is limited because of the one-step prediction horizon. This article proposes an event-triggered distributed model predictive control algorithm for such systems. The online computational burden is alleviated within the distributed framework through the use of an event-triggered mechanism and a variable prediction horizon approach. These strategies not only reduce the number of optimization problems requiring online resolution and simplify them, but also allow for a balance between the control performance and the online computational burden by adjusting event-triggering thresholds. The algorithm utilizes state tubes and terminal sets that are tailored to the characteristics of the piecewise affine systems, thereby rigorously establishing the recursive feasibility of the optimization problems and the stability of the closed-loop system. The simulation results validate the effectiveness of the proposed algorithm.

关键词： distributed model predictive control event-triggered mechanism piecewise affine systems variable prediction horizon

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