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Improved Capon Estimator for High-Resolution DOA Estimation and Its Statistical Analysis

IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1716-1729页

作者： Weiliang Zuo Jingmin Xin Changnong Liu Nanning Zheng Akira Sano IEEE the National Key Laboratory of Human-Machine Hybrid Augmented Intelligence the National Engineering Research Center for Visual Information and Applicationsand the Institute of Artificial Intelligence and RoboticsXi’an Jiaotong UniversityXi’an 710049China the Data Center China Construction BankBeijing 100033China the Department of System Design Engineering Keio UniversityYokohama 223-8522Japan

Despite some efforts and attempts have been made to improve the direction-of-arrival(DOA)estimation performance of the standard Capon beamformer(SCB)in array processing,rigorous statistical performance analyses of these modified Capon estimators are still *** paper studies an improved Capon estimator(ICE)for estimating the DOAs of multiple uncorrelated narrowband signals,where the higherorder inverse(sample)array covariance matrix is used in the Capon-like cost *** establishing the relationship between this nonparametric estimator and the parametric and classic subspace-based MUSIC(multiple signal classification),it is clarified that as long as the power order of the inverse covariance matrix is increased to reduce the influence of signal subspace components in the ICE,the estimation performance of the ICE becomes equivalent to that of the MUSIC regardless of the signal-to-noise ratio(SNR).Furthermore the statistical performance of the ICE is analyzed,and the large-sample mean-squared-error(MSE)expression of the estimated DOA is *** the effectiveness and the theoretical analysis of the ICE are substantiated through numerical examples,where the Cramer-Rao lower bound(CRB)is used to evaluate the validity of the derived asymptotic MSE expression.

关键词： Capon beamformer direction-of-arrival(DOA)estimation large-sample mean-squared-error(MSE) subspace-based methods uniform linear array

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Collaboration of spatial and feature attention for visual tracking

Collaboration of spatial and feature attention for visual tr...

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2009 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Hong Liu Weiwei Wan Ying Shi Key Laboratory of Machine Perception and Intelligence and the Key Laboratory of Integrated Micro-System Shenzhen Graduate School Peking University China Key Laboratory of Machine Perception and Intelligence Peking University China

Although primates can facilely maintain long-duration tracking of an object without infection of occlusion or other near similar distracters, it remains a challenge for computer vision system. Studies in psychology suggest that the ability of primates to focus selective attention on the spatial properties of an object is necessary to observe object quickly and efficiently while focus selective attention on the feature properties of object is necessary to render it more prominent from the distracters. In this paper, we propose a novel spatial-feature attentional visual tracking (SFAVT) algorithm to encode both. In SFAVT, tracking is treated as an on-line binary classification problem where spatial attention is employed in early selective procedure to construct foreground/background appearance model by identifying image patches with good localization properties, and in late selective procedure to update models by maintaining image patches with good discrimitive motion properties. Meanwhile, feature attention works in mode seeking procedure to help select feature spaces that best separate a target from background. The on-line tuned adaptive appearance models by those selected feature spaces are used to train a classifier for target localization, then. Experiments under various real-world conditions show that this algorithm is able to track an object influenced by dramatic distracters while is of comparable time efficiency with meanshift.

关键词： Target tracking Shape Computer vision Psychology machine intelligence Intelligent robots USA Councils International collaboration machine vision Surveillance

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Quantized robust H-two filtering for Markovian jump linear systems over networks with nonaccessible mode information

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控制理论与应用（英文版） 2011年第4期9卷 505-512页

作者： Tao LIU Qijun CHEN Hao ZHANG Iko MIYAZAWA Department of Electronics and Information Engineering Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai 201804 China Department of Machine Control Technology Kanagawa Industrial Technology Center Kanagawa 243-0435 Japan

This paper is concerned with the problems of H-two filtering for discrete-time Markovian jump linear systems subject to logarithmic quantization. We assume that only the output of the system is available, and therefore the mode information is nonaccessible. In this paper, a mode-independent quantized H-two filter is designed such that filter error system is stochastically stable. To this end, sufficient conditions for the existence of an upper bound of H-two norm are presented in terms of linear matrix inequalities. Considering uncertainty of system matrices, a robust H-two filter is designed. The proposed method is also applicable to cover the case where the transition probability matrix is not exactly known but belongs to a given polytope. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed approach.

关键词： Markovian jump linear systems Quantized robust H-two filter Mode independent Sector bound approach Linear matrix inequalities

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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced control Applications

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 18-36页

作者： Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis IEEE the Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protectionand Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China the School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China the Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA the School of Information and Control Engineering Liaoning Petrochemical UniversityFushun 113001China the UTA Research Institute the University of Texas at ArlingtonArlington TX 76118 USA

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

关键词： Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)

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Improving Video Moment Retrieval by Auxiliary Moment-Query Pairs with Hyper-Interaction

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IEEE Transactions on Circuits and systems for Video Technology 2024年第5期35卷 3940-3954页

作者： Zeng, Runhao Zhuo, Yishen Li, Jialiang Yang, Yunjin Wu, Huisi Chen, Qi Hu, Xiping Leung, Victor C. M. Shenzhen MSU-BIT University Artificial Intelligence Research Institute China Guangdong-Hong Kong-Macao Joint Laboratory For Emotional Intelligence And Pervasive Computing Shenzhen518172 China Shenzhen University Guangdong Key Laboratory Of Electromagnetic Control And Intelligent Robots College Of Mechatronics And Control Engineering Shenzhen518060 China Shenzhen University College Of Computer Science And Software Engineering Shenzhen518060 China University Of Adelaide Australian Institute For Machine Learning Adelaide5005 Australia

Most existing video moment retrieval (VMR) benchmark datasets face a common issue of sparse annotations-only a few moments being annotated. We argue that videos contain a broader range of meaningful moments that, if leveraged, could significantly enhance performance. Existing methods typically follow a generate-then-select paradigm, focusing primarily on generating moment-query pairs while neglecting the crucial aspect of selection. In this paper, we propose a new method, HyperAux, to yield auxiliary moment-query pairs by modeling the multi-modal hyper-interaction between video and language. Specifically, given a set of candidate moment-query pairs from a video, we construct a hypergraph with multiple hyperedges, each corresponding to a moment-query pair. Unlike traditional graphs where each edge connects only two nodes (frames or queries), each hyperedge connects multiple nodes, including all frames within a moment, semantically related frames outside the moment, and an input query. This design allows us to consider the frames within a moment as a whole, rather than modeling individual frame-query relationships separately. More importantly, constructing the relationships among all moment-query pairs within a video into a large hypergraph facilitates selecting higher-quality data from such pairs. On this hypergraph, we employ a hypergraph neural network to aggregate node information, update the hyperedge, and propagate video-language hyper-interactions to each connected node, resulting in context-aware node representations. This enables us to use node relevance to select high-quality moment-query pairs and refine the moments' boundaries. We also exploit the discrepancy in semantic matching within and outside moments to construct a loss function for training the HGNN without human annotations. Our auxiliary data enhances the performance of twelve VMR models under fully-supervised, weakly-supervised, and zero-shot settings across three widely used VMR datasets: Activi

关键词： Query languages

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Brain-inspired Intelligent Robotics:Theoretical Analysis and systematic Application

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machine intelligence Research 2023年第1期20卷 1-18页

作者： Hong Qiao Ya-Xiong Wu Shan-Lin Zhong Pei-Jie Yin Jia-Hao Chen The State Key Laboratory of Management and Control for Complex System Institute of AutomationChineseAcademyof SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Chinese Academy of Science Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031China School of Mechanical Engineering University of Science and Technology BeijingBeijing 100083China

Traditional joint-link robots have been widely used in production lines because of their high precision for single *** the development of the manufacturing and service industries,the requirement for the comprehensive performance of robotics is *** types of bio-inspired robotics have been investigated to realize human-like motion control and manipulation.A study route from inner mechanisms to external structures is proposed to imitate humans and animals *** this idea,a brain-inspired intelligent robotic system is constructed that contains visual cognition,decision-making,motion control,and musculoskeletal *** paper reviews cutting-edge research in brain-inspired visual cognition,decision-making,motion control,and musculoskeletal *** software systems and a corresponding hardware system are established,aiming at the verification and applications of next-generationbrain-inspired musculoskeletal robots.

关键词： Brain-inspired intelligent robot software and hardware decision making muscle control cognitive intelligence.

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Euler-Discretized GZ-Type Complex Neuronet Computing Real-Time Varying Complex Matrix Inverse 36

Euler-Discretized GZ-Type Complex Neuronet Computing Real-Ti...

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第36届中国控制会议

作者： Yunong Zhang Guofu Wu Binbin Qiu Wan Li Penghao He School of Information Science and Technology Sun Yat-sen University(SYSU) Key Laboratory of Autonomous Systems and Networked Control Ministry of Education SYSU-CMU Shunde International Joint Reseach Institute Key Laboratory of Machine Intelligence and Advanced Computing(Sun Yat-sen University) Ministry of Education

ISBN: (纸本)9781538629185

In this paper,a GZ-type complex neuronet（generated by combining gradient dynamic system and Zhang dynamic system） is illustrated and discretized into an Euler-discretized（i.e.,discretized by Euler forward rule） GZ-type complex neuronet for computing real-time varying complex matrix *** results not only show the efficacy of the proposed Eulerdiscretized GZ-type neuronet but also verify that the error pattern is square.

关键词： GZ-Type Neuronet Complex Matrix Inverse Euler Forward Rule Computer Simulation Error Pattern

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An effective background reconstruction method for complicated traffic crossroads

An effective background reconstruction method for complicate...

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IEEE International Conference on systems, Man and Cybernetics

作者： Hong Liu Wei Chen Key Laboratory of Machine Perception and Intelligence Key Laboratory of Integrated Micro-System Shenzhen Graduate School Peking University China Key Laboratory of Integrated Micro-System Key Laboratory of Machine Perception and Intelligence Shenzhen Graduate School Peking University China

Effective background reconstruction is the key for real time traffic flow monitoring. High traffic density and complexity of background scene make reconstruction more difficult. Background estimation based on the median method is imprecise under a complex traffic flow condition. In this paper, a new background estimation method based on the similarity of background using parameters of gray mean and variance is proposed. Therefore, a two-dimensional clustering and merging mechanism is introduced. At last, accurate decision about the category of the background is made by analyzing the distribution characteristic of the frame numbers in one category. Our algorithm works on the difficult condition of traffic congestion with higher reliability. The proposed method can be used in background reconstruction of the crossroads based on video sequences.

关键词： Reconstruction algorithms Layout Video sequences Laboratories machine intelligence Image reconstruction Frequency Image motion analysis Gray-scale Clustering algorithms

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An Extended-Isomap for high-dimensional data accuracy and efficiency: a comprehensive survey

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Multimedia Tools and Applications 2024年第38期83卷 85523-85574页

作者： Yousaf, Mahwish Shakoor Khan, Muhammad Saadat Ullah, Shamsher Institute of Intelligence Machine Hefei Institutes of Physical Science Chinese Academy of Sciences Anhui Hefei230027 China Key Laboratory of Materials Physics Institute of Solid-State Physics Chinese Academy of Sciences Anhui Hefei230027 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Guangdong Shenzhen518060 China

Manifold learning is a widely adopted nonlinear dimensionality reduction technique employed to discover low-dimensional representations from high-dimensional data and to explore the intrinsic data structure. It encompasses a range of nonlinear techniques, including Isomap, Local Linear Embedding (LLE), Local Tangent Space Alignment (LTSA), and Multidimensional Scaling (MDS), among others. Isomap, as a popular method in manifold learning, has exhibited promising results. However, it encounters several challenges, such as the Topological Stability Problem, Shortest Path Distance, and noise sensitivity, which compromise its accuracy and elevate its computational demands. This survey paper presents three novel existing approaches to address these challenges and enhance the performance of Isomap. Firstly, the FastIsomap method, an existing approach that combines state-of-the-art algorithms like the KD tree and NN-descent to increase graph accuracy while reducing computational cost. Secondly, the FastIsomapVis method, also an existing technique, employs a hierarchical divide-and-conquer strategy employing the KD tree and Dijkstra Buckets Double, which enhances accuracy and reduces computational time in Isomap. Lastly, the NR-Isomap method, another existing approach, used the Local Tangent Space Alignment algorithm to remove noise sensitivity and short-circuit edge problems. The existing methods improve the accuracy of Isomap but also streamline its computational requirements. Furthermore, this survey paper discusses the open issues and future research directions for Isomap and manifold learning methods. It can be a valuable resource for researchers seeking insights across diverse domains. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Clustering algorithms

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Robot-CT Scanning Oriented Synchronous Trajectory Planning of a Dual-Manipulator system 42

Robot-CT Scanning Oriented Synchronous Trajectory Planning o...

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42nd Chinese control Conference, CCC 2023

作者： Zhang, Shuaikang Yuan, Mingxing Zhang, Xuebo Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing400065 China

ISBN: (纸本)9789887581543

At present, most CT scanning systems adopt the traditional horizontal O-frame, suspension or C-arm structures, which can not balance the flexibility and functionality. With the development of robot technology, CT scanning systems based on manipulators have gradually emerged. However, limited by the motion accuracy of the manipulator, most researchers sacrifice the flexibility or increase the mass to improve the accuracy. To overcome this limitation, a new master-slave teaching-based scanning method is proposed to improve the scanning accuracy of the dual-manipulator Robot-CT system with the auxiliary function of rigid links. First, a rigid link is employed to connect the end effectors of the two manipulators. Next, the sampled trajectory of each joint of the slave-manipulator is recorded while the master-manipulator pulls the slave-manipulator to perform a circular motion. Finally, when carrying out the scanning, the dual-manilupator system reproduces the recorded joint trajectory without the rigid element, thereby improving the accuracy of the dual-manipulator CT scanning system to achieve a high-accuracy spatiotemporal synchronization and alignment of pose. To this end, a fifth-order spline interpolation is used to interpolate the sampled trajectory of each joint of the slave-manipulator, which allows it to perfectly reproduce the joint trajectory recorded during the teaching process and ensures the smoothness of the angular velocity and acceleration curves. Simulations are investigated and the corresponding results confirm the effectiveness of the trajectory planning method of the slave-manipulator. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Manipulators

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