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检索条件"机构=the State Key Laboratory of Management and Control for Complex Systems.Institute of Automation"

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Image Clustering Based on Deep Sparse Representations

Image Clustering Based on Deep Sparse Representations

引用

IEEE Symposium Series on Computational Intelligence

作者： Le Lv Dongbin Zhao Qingqiong Deng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China College of Information Science and Technology Beijing Normal University Beijing 100875 China

ISBN: (纸本)9781509042418

Currently, the supervised trained deep neural networks (DNNs) have been successfully applied in several image classification tasks. However, how to extract powerful data representations and discover semantic concepts from unlabeled data is a more practical issue. Unsupervised feature learning methods aim at extracting abstract representations from unlabeled data. Large amount of research works illustrate that these representations can be directly used in the supervised tasks. However, due to the high dimensionality of these representations, it is difficult to discover the categorical concepts among them in an unsupervised way. In this paper, we propose combining the winner-take-all autoencoder with the bipartite graph partitioning algorithm to cluster unlabeled image data. The winner-take-all autoencoder can learn the additive sparse representations. By the experiments, we present the properties of the sparse representations. The bipartite graph partitioning can take full advantage of them and generate semantic clusters. We discover that the confident instances in each cluster are well discriminated. Based on the initial clustering result, we further train a support vector machine (SVM) to refine the clusters. Our method can discover the categorical concepts rapidly and the experiment shows that the clustering performance of our method is good.

关键词： supervised trained deep

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Automatic Busbar Detection in Substation: Using Directional Gaussian Filter, Gradient Density, Hough Transform and Adaptive Dynamic K-means Clustering 34

Automatic Busbar Detection in Substation: Using Directional ...

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第三十四届中国控制会议

作者： CHEN Hongkai SUN Shiying WANG Tianzheng ZHAO Xiaoguang TAN Min The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences State Grid Shanxi Electric Power Research Institute

ISBN: (纸本)9781467374439

As the power system developing towards the extra-high-voltage(EHV), ultra-high-voltage(UHV), and large capacity direction in China, online monitoring becomes much more vital for power equipment to ensure the safe operation of power system. The computer vision-based Equipment Map state Detection technique can capture the abnormal status of power *** busbar, as a intermediate link at all levels of voltage distribution device, is vital in system safety and stability *** this paper, we propose an automatic busbar detection method in an image for substation using directional Gaussian lter to strengthen horizontal linear target in an image, gradient density to generate a busbar con dence map, Hough Transform to detect straight lines and adaptive dynamic K-means clustering to get closed lines for optimizing. Then, the busbar can be marked in image and it can be used for further checking whether there are foreign things hanging on the busbar. Experiments on some images taken in several substations demonstrate that our method is effective.

关键词： Busbar Detection,Directional Gaussian Filter,Gradient Density,Hough Transform,Adaptive Dynamic K-means Clustering

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Iterative Q-learning-based nonlinear optimal tracking control

Iterative Q-learning-based nonlinear optimal tracking contro...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Qinglai Wei Ruizhuo Song Yancai Xu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9781509042418

A new Q-learning algorithm is developed for a class of discrete-time nonlinear systems in this paper to solve the infinite horizon optimal tracking problems. Using system transformations, the optimal tracking problem is transformed to be an optimal regulation problem. Thereafter, for the regulation system, the new Q-learning algorithm is developed in order to obtain the optimal control law. Convergence of the iterative Q functions and the admissibility of the iterative control law are analyzed. In the end, two corresponding simulation examples are presented to illustrate the performance of the newly developed algorithm.

关键词： optimal control convergence discrete time systems iterative learning control nonlinear control systems

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An answer recommendation algorithm for medical community question answering systems

An answer recommendation algorithm for medical community que...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Jing Wang Chuntao Man Yifei Zhao Feiyue Wang College of Automation Harbin University of Science & Technology Harbin Heilongjiang Province China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509029280

Online medical community question answering (cQA) systems are playing important roles as a supplement of the traditional medical service systems. The answer recommendation service provides guidance to diagnose diseases and brings convenience and valuable reference to users. In this paper, we propose a method to recommend answer for particular questions on medical cQA system. There are three steps for the answer recommendation system, including similar cases retrieval, answers quality estimation and answer recommendation. The proposed algorithm is tested on a dataset collected from online medical community question answering system. The results show a good performance in answer recommendation.

关键词： Medical services Estimation Feature extraction Training Medical diagnostic imaging Knowledge discovery History

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High-precision NURBS interpolation algorithm based on the bisection method 34

High-precision NURBS interpolation algorithm based on the bi...

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34th Chinese control Conference, CCC 2015

作者： Zhongyi, Zheng Chao, Yang Fengshui, Jing Guodong, Yang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789881563897

For a high precision Non-Uniform Rational B-Spline (NURBS) interpolator, calculating the parameter of the next path interpolating point is an indispensable step, which affects feedrate fluctuation. This paper presents a new, simple and precise interpolation algorithm for parameter curve which adopts first-order Taylor's expansion, and then make use of the bisection method to achieve accurate path parameters. In the meanwhile, the interpolator is restricted from geometric and kinematical constraints. A simulation study is conducted to demonstrate the advantages of proposed interpolation algorithm compared with other algorithms for the parametric curves represented in the NURBS form. © 2015 Technical Committee on control Theory, Chinese Association of automation.

关键词： Interpolation Machining NURBS Precision

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The Energy Consumption Analysis of Hydraulic Quadruped Robot based on Gait Parameters 34

The Energy Consumption Analysis of Hydraulic Quadruped Robot...

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第三十四届中国控制会议

作者： ZONG Xiaoyan Wang Shoukun Wang Junzheng Chen Guangrong Zhang Xiaoling State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

ISBN: (纸本)9781467374439

The optimization of the energy consumption is one of the most important problems that face the designers of mobile robots. This implies that it is significant to analyze the energy consumption of hydraulic quadruped robot under different gait parameters. In this paper, the kinematics and dynamics models of a hydraulic quadruped robot are established firstly. Then, the length of step, the height of step, the height of center of mass, and the duty ratio of gait cycle are set as the primary research points about the energy consumption of mobile robot. In addition, the energy consumptions of the feet with and without mechanical springs are compared and analyzed. In order to get the visual observation of energy cost in the hydraulic quadruped robot during a waking cycle and the best set of locomotion variables that achieve the energy optimization, related simulations are done for gait parameters. Finally, the results provide a recommendation for the gait planning of the hydraulic quadruped robot, that is, the quadruped robot should walk with a relatively long step length, a relatively low height of step, a relatively high height of center of mass, and a relatively small duty ratio of gait cycle.

关键词： Hydraulic quadruped robot Kinematics Dynamics Gait parameters Energy consumption

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Event-triggered consensus and passification co-design for multi-agent systems over unreliable communication networks

Event-triggered consensus and passification co-design for mu...

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American control Conference

作者： Chao Ma Hong Qiao School of Automation and Electrical Engineering University of Science and Technology Beijing 100083 China State Key Lab of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467386838

In this paper, the event-triggered communication strategy with passification consensus co-design is investigated for a class of general multi-agent systems. In particular, the proposed event-triggered mechanism is asynchronous for each agent individually such that the information exchange cost can be reduced effectively. Moreover, with the consideration of unreliable communication networks, randomly occurring transmission failure is modeled by utilizing the stochastic variable. Based on passivity theory, sufficient conditions are established to guarantee that the consensus can be achieved with the desired passification performance. Furthermore, the consensus protocol gain is designed. Finally, a numerical example is provided to demonstrate the effectiveness of our theoretical results.

关键词： Multi-agent systems Symmetric matrices Communication networks Stochastic processes Protocols Eigenvalues and eigenfunctions Information exchange networks(communications) Multi-agent systems information exchange Symmetric matrix Eigenfunctions Markov chain Telecommunications protocols Event trigger Co-design passivity theory Stochastic Processes

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Abnormal interhemispheric resting-state functional connectivity in primary open-angle glaucoma

Abnormal interhemispheric resting-state functional connectiv...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Peng Zhou Jieqiong Wang Ting Li Ningli Wang Junfang Xian Huiguang He State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences and University of Chinese Academy of Sciences Beijing China Beijing Tongren Hospital Capital Medical University Beijing China

ISBN: (纸本)9781457702198

Glaucoma is the second leading cause of blindness and it has been the topic of massive studies to explore the underlying mechanisms of the disease. Resting-state neuroimaging studies have been widely applied to investigate the functional damage of the brain, but little is known about the alterations of the interhemispheric resting-state functional connectivity (RSFC) in patients with primary open-angle glaucoma (POAG). In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to explore the interhemispheric RSFC of the brain in POAG patients. The result showed decreased VMHC in the precuneus and the occipital lobe including calcarine and cuneus, as well as increased VMHC in the lingual gyrus, insula, supramarginal gyrus, and frontal gyrus. Meanwhile, we found the mean VMHC in precuneus was negatively correlated (r=-0.551, P=0.041) with Cup-to-disk Ratio. Significant differences between POAG patients and normal controls reveal the altered brain regions and the functional damage, strengthening the understanding of the primary open-angle glaucoma.

关键词： Visualization Correlation Diseases Optical imaging Retina Magnetic resonance imaging Brain

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Spatial-temporal context-aware abnormal event detection based on incremental sparse combination learning

Spatial-temporal context-aware abnormal event detection base...

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World Congress on Intelligent control and automation (WCICA)

作者： Hongkai Chen Xiaoguang Zhao Tianzheng Wang Min Tan Shiying Sun State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China State Grid Shanxi Electric Power Research Institute Taiyuan China

ISBN: (纸本)9781467384155

Real-time abnormal event detection in practical video surveillance has been a difficult task, because there are a huge amount of continuous arrival video data, where normal events may change and only a small portion of video data contains abnormal events. In this paper, to address this problem, we use the latter arrived data to online update our model in an incremental way. We propose a spatial-temporal context-aware abnormal event detection method based on incremental sparse combination learning (ISCL). To better represent an event, we propose a novel Gradient Local Binary Patterns on Orthogonal Planes (GLBPOP) which is extracted by combining 3D gradient information and spatial-temporal context information together on two orthogonal planes. Then we propose an ISCL framework to update each dictionary in combination set in an incremental way to adapt to the possible varied upcoming normal samples. Experiments on public dataset demonstrate the proposed method is effective and superior.

关键词： Dictionaries Hidden Markov models Context Event detection Three-dimensional displays Data models Feature extraction

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An overall solution of Virtual Reality classroom

An overall solution of Virtual Reality classroom

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Xisong Dong Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509029280

Virtual Reality (VR) is a three-dimensional computer-generated virtual world. It is essential to introduced VR technology to education area to develop new teaching mode to improve the efficiency and quality of teaching and learning. Among them, VR classroom has quickly become most dazzling star with its subversive advantage. This paper proposes an overall integration solution of VR classroom, including its composition, its scene design of various disciplines and its main advantage. Finally, a case study of a geography lesson is provided to show its advantages and strong potentiality.

关键词： Education Virtual reality Geography Three-dimensional displays Visualization Solar system Chemistry

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