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Knowledge As Not Only Justified True Beliefs in Vision

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 297-299页

作者： Wenbo Zheng Fei-Yue Wang IEEE School of Computer Science and Artificial Intelligence Wuhan University of Technology Sanya Science and Education Innovation Park of Wuhan University of Technology the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences

COMPUTATIONAL knowledge vision [1] is emphasized as a novel perspective or field in this paper. It first proposes the visual hierarchy and its connection to knowledge, stating that knowledge is a justified true belief. To further the previous research, we concisely summarize our recent works and suggest a new direction that knowledge is also a thought framework in vision.

关键词： Computational modeling Visualization Artificial intelligence Data models Visual perception Visual databases Training data

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Optimal crater landmark selection based on optical navigation performance factors for planetary landing

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Chinese Journal of Aeronautics 2023年第3期36卷 254-270页

作者： Yi XIU Shengying ZHU Rui XU Maodeng LI School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Ministry of Industry and Information TechnologyBeijing 100081China Key Laboratory of Dynamics and Control of Flight Vehicle Ministry of EducationBeijing 100081China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control EngineeringBeijing 100091China

Planetary craters are natural navigation landmarks that widely exist and are easily *** navigation based on crater landmarks has become an important autonomous navigation method for planetary *** to the increase in observed crater landmarks and the limitation of onboard computation,the selection of good crater landmarks has gradually become a research hotspot in the field of landmark-based optical *** paper designs a fast crater landmark selection method,which not only considers the configuration observability of crater subsets but also focuses on the influence on navigation performance arising from the measurement uncertainty and the matching confidence of craters,which is different from other landmark selection *** factor of measurement uncertainty,which is anisotropic,correlated and nonidentically distributed,is quantified and integrated into selection based on crater pairing detection and localization error *** addition,the concept of the crater matching confidence factor is introduced,which reflects the possibility of 2D projection measurements corresponding to 3D *** with the configuration observability factor,the crater landmark selection indicator is ***,the effectiveness of the proposed method is verified by Monte Carlo simulations.

关键词： Crater-based optical navigation Crater landmark selection Crater matching Measurement uncertainty Planetary landing

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Calibration of the Solar X-ray Detector on-board the Macao science Satellite-1B for Soft X-ray Detection

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science China Earth sciences 2025年第1期68卷 11-26页

作者： Man-Hei NG Xiaoping ZHANG Jianwu CHEN Yongqiang SHI Fuchang ZUO Wenxi PENG Weichun FU Liansheng LI Pengwei LUO Chi-Long TANG Guozheng ZHANG Zhiwu MEI Li WANG Cunhui LI Jiaming OU Yanyan Xu State Key Laboratory of Lunar and Planetary Sciences Macao University of Science and TechnologyMacao999078China Space Optoelectronic Measurement and Perception Laboratory Beijing Institute of Control EngineeringBeijing100190China Institute of High Energy Physics Chinese Academy of SciencesBeijing100049China Science and Technology on Vacuum Technology and Physics Laboratory Lanzhou Institute of PhysicsLanzhou730000China China National Space Administration(CNSA) Macao Center for Space Exploration and ScienceMacao999078China

The Solar X-ray Detector(SXD)on-board the Macao science Satellite-1B(MSS-1B)was successfully launched via the Chinese Long March-2C rocket on 21 May 2023,and commenced operations in early June of the same *** MSS-1B/Soft X-ray Detection Units(SXDUs)employ two silicon drift detectors(SDDs),providing a wide range of energy spectra spanning from 0.7 to 24 ***,the SXDUs deliver a high-resolution capability of 0.14 keV@5.9 keV and operate with a time cadence of 1 ***,we perform thorough calibrations of the MSS-1B/SXDUs,employing a combination of ground experiments and *** addition,quantitative analysis comparing the flux measurements obtained by the MSS-1B/SXDUs to the data collected by the Geostationary Operational Environmental Satellite(GOES),provides compelling evidence of their ***,the preliminary spectral analysis results showcase the robustness and expected performance of the MSS-1B/SXDUs,unlocking their potential for facilitating the study of dynamic evolution of solar ***,the innovative MSS-1B/Solar X-ray Detector facilitates concurrent observations of solar soft and hard X-rays,thereby making valuable contributions to the advancements in solar research.

关键词： Macao science Satellite-1B(MSS-1B) Calibration Solar X-Ray Detector Spectrometer Soft X-rays Solar flares Solar abundances

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Surface-PMSM Sensorless control Strategy Based on Reduced-Order Linear Kalman Filter Cooperating With Prediction Error Rolling Compensation

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IEEE Transactions on Power Electronics 2025年第8期40卷 10804-10815页

作者： Xu, Sang Shen, Anwen Tang, Qipeng Wang, Miaomiao Luo, Pan Luo, Xin Xu, Jinbang National Key Laboratory of Science and Technology on Multispectral Information Processing Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China

Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors due to its strong robustness against measurement and system noise. However, the conventional method suffers from poor position and speed estimation accuracy under dynamic conditions and high computational cost. In order to solve these problems, an enhanced sensorless control strategy based on reduced-order linear Kalman filter (RLKF) cooperating with prediction error rolling compensation is introduced in this article. Differing from conventional methods, a reduced-order linear state equation encompassing rotor position, speed, and torque disturbance is constructed. Then, by obtaining the prediction error of system output using the motor current equation in the predictive reference frame, the optimal estimation of rotor position and speed in the KF algorithm is achieved based on the reduced-order model. This not only simplifies the calculation process but also enhances the position and speed estimation accuracy under dynamic conditions. Meanwhile, a prediction error rolling compensation algorithm is developed to minimize the estimation deviations caused by motor parameter variations. In addition, the system's dynamic performance is further improved with an adopted speed controller based on torque disturbance feedforward and acceleration feedback. Finally, experimental results verify the effectiveness and feasibility of the proposed strategy. © 1986-2012 IEEE.

关键词： Permanent magnets

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Parameter-Free Shifted Laplacian Reconstruction for Multiple Kernel Clustering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1072-1074页

作者： Xi Wu Zhenwen Ren F.Richard Yu the School of National Defence Science and Technology Southwest University of Science and TechnologyMianyang 621010China the School of National Defence Science and Technology Southwest University of Science and TechnologyMianyang 621010 the Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou UniversityWuzhou 543002 the Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518060China

Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian *** MKC can effectively cluster nonlinear data,but it faces two main challenges:1)As an unsupervised method,it is up against parameter problems which makes the parameters intractable to tune and is unfeasible in real-life applications;2)Only considers the clustering information,but ignores the interference of noise within Laplacian.

关键词： parameter letter Parameter

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Rapid Autonomous Navigation of Geosynchronous Satellite Using Novel Infrared Earth Measurements 42

Rapid Autonomous Navigation of Geosynchronous Satellite Usin...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Xiaoxiang Shi, Heng Wang, Shuo Wei, Chunling Xiong, Kai Beijing Institute of Control Engineering Beijing100094 China Science and Technology on Space Intelligence Control Laboratory Beijing100094 China

ISBN: (纸本)9789887581543

This paper presents a rapid autonomous navigation technology for Earth satellites using static infrared Earth sensor (SIES). Conventional Earth sensor has limitations in target and background segmentation, geocentric vector direction extraction, and interference rejection. A novel SIES sensor design is proposed that incorporates new technologies to increase light transmittance, reduce circuit noise, and improve image processing and attitude determination algorithms. This enables higher angular accuracy and new geocentric distance measurement information, resulting in significantly improved satellite attitude measurement accuracy of ±0. 01 °. The rapid autonomous navigation system framework for Geosynchronous (GEO) satellites using novel geocentric measurements by SIES is presented, including observability analysis, accuracy metrics acquisition, and autonomous navigation information fusion algorithms. This technology has been successfully verified on China's new generation of geosynchronous orbit satellite platform, as well as other Earth-centered orbit types. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Orbits

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Digitally-Assisted Analog Self-Interference Cancellation for STAR System

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China Communications 2025年第3期22卷 36-53页

作者： Pan Wensheng Shi Chengzhe Li Tong Shen Ying Shao Shihai National Key Laboratory of Wireless Communications University of Electronic Science and Technology of ChinaChengdu 611731China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing 100089China

To enable simultaneous transmit and receive(STAR)on the same frequency in a densely deployed space with multi-interference sources,this work proposes a digitally-assisted analog selfinterference cancellation method,which can acquire reference signals through flexible wired/wireless switching *** on this method,the Minimum Mean Square Error algorithm with known channel state information is derived in detail,determining the upper limit of the cancellation performance,and the Adaptive Dithered Linear Search algorithm for real-time engineering cancellation is *** correctness of theoretical analysis is verified by the practical self-interference channel measured by a vector network ***,we have designed and implemented the corresponding multiinterference cancellation prototype with the digitallyassisted structure,capable of handling multiple interferences(up to three)and supporting a large receive bandwidth of 100 MHz as well as a wide frequency coverage from 30 MHz to 3000 *** test results demonstrate that in the presence of three interferences,when the single interference bandwidth is 0.2/2/20 MHz(corresponding to the receive bandwidth of 2/20/100 MHz),the cancellation performance can reach 46/32/22 dB or more.

关键词： analog self-interference cancellation channel measurement digitally-assisted multiinterference prototype design simultaneous transmit and receive

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Adjustable patch and feature prior token-based transformer for weakly supervised semantic segmentation

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International Journal of Computers and Applications 2024年第7期46卷 445-454页

作者： Li, Linjuan Zhang, Haoxue Xie, Gang Bai, Yanhong School of Electronic and Information Engineering Taiyuan University of Science and Technology Taiyuan China Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan China

Weakly supervised semantic segmentation is a challenging task, utilizing only low-cost weak supervision to produce pixel-level predictions. Existing transformer-based methods for weakly supervised semantic segmentation have some limitations: (1) Fixing patch size might destroy the structured semantics, which is unfriendly to objects of different scales, and (2) Ignoring the prior features when using multi-head attention mechanisms might lead to inaccurate segmentation localization. To tackle these issues, we proposed an effective transformer framework coupled with the adjustable patch and prior feature tokens, termed as APFPformer, in which an adjustable patch module is developed to split the image according to the area of the salient object for preserving the structured semantics in patches. A prior feature token module is devised to exploit the edge and texture information as prior tokens, ensuring the gain of discriminative representation. Additionally, a single-stage scheme is applied to reduce the computation and rapid segmentation process. Our experiments demonstrate the superiority of our approach over early methods, gaining competitive mean Intersection-over-Union scores of 67.9% on the PASCAL VOC2012 dataset and 40.2% on the MS COCO dataset. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Semantic Segmentation

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Short-Term Residential Load Forecasting via Pooling-Ensemble Model with Smoothing Clustering

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial intelligence 2024年第7期5卷 3690-3702页

作者： Xiao, Jiang-Wen Fang, Hongliang Wang, Yan-Wu Huazhong University of Science and Technology Ministry of Education School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China

Short-term residential load forecasting is essential to demand side response. However, the frequent spikes in the load and the volatile daily load patterns make it difficult to accurately forecast the load. To deal with these problems, this article proposes a smoothing clustering method for daily load clustering and a pooling-ensemble model for one day ahead load forecasting. The whole short-term load forecasting framework in this article contains three steps. Specifically and first, the states of the residents are obtained by clustering the daily load curves with the proposed smoothing clustering method. Second, a weighted mixed Markov model is built to predict the probability distribution of the load state in the next day. Third, multiple predictors in the pooling-ensemble model are selected for different states and the load is forecasted by weighing the results of the multiple predictors based on the predicted states. Results of the case studies and comparison studies on two public datasets verify the advantages of the smoothing clustering method and the pooling-ensemble model. © 2020 IEEE.

关键词： Probability distributions

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Dynamic Movement Primitives Based Robot Skills Learning

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Machine intelligence Research 2023年第3期20卷 396-407页

作者： Ling-Huan Kong Wei He Wen-Shi Chen Hui Zhang Yao-Nan Wang School of Intelligence Science and Technology University of Science and Technology BeijingBeijing 100083China Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China School of Robotics and the National Engineering Laboratory of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

In this article,a robot skills learning framework is developed,which considers both motion modeling and *** order to enable the robot to learn skills from demonstrations,a learning method called dynamic movement primitives(DMPs)is introduced to model motion.A staged teaching strategy is integrated into DMPs frameworks to enhance the generality such that the complicated tasks can be also performed for multi-joint *** DMP connection method is used to make an accurate and smooth transition in position and velocity space to connect complex motion *** addition,motions are categorized into different goals and *** is worth mentioning that an adaptive neural networks(NNs)control method is proposed to achieve highly accurate trajectory tracking and to ensure the performance of action execution,which is beneficial to the improvement of reliability of the skills learning *** experiment test on the Baxter robot verifies the effectiveness of the proposed method.

关键词： Dynamic movement primitives(DMPs) trajectory tracking control robot learning from demonstrations neural networks(NNs) adaptive control

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