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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Xikai Tu Jian Huang Jiping He Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China School of Biological and Health Systems Engineering Arizona State University Tempe AZ USA School of Mechatronic Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509033652

To regain mobility, stroke patients need to receive repetitive and intensive therapy. Robot-assisted rehabilitation is an active area of research. Cheap robotic leg rehabilitation devices should be developed to meet the demands and assist most patients. A low cost hip-knee exoskeleton prototype powered by pneumatic muscles was developed. On this basis, Functional Electrical Stimulation (FES) induced paralyzed muscles to realize ankle joint rehabilitation training. As both of pneumatic muscle and FES induced muscle possess highly nonlinear characteristics, a sliding control algorithm called Chattering mitigation Robust Variable control (CRVC) was applied to leg hybrid rehabilitation. The combination of exoskeleton and FES is a promising way to reduce the cost and the complexity of designing hip-knee-ankle exoskeleton. The proposed hybrid method is verified by treadmill-based gait training experiments.

关键词： Muscles Exoskeletons Mathematical model Legged locomotion Iron Training

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Multi-agent containment control with input saturation on switching topologies

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IET control Theory and Applications 2015年第3期9卷 399-409页

作者： Su, Housheng Chen, Michael A.Q. School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan430074 China Department of Mechanical Engineering University of Hong Kong Hong Kong Hong Kong

This study aims to investigate containment control of linear multi-agent systems with input saturation on switching topologies. For such a multi-agent system, both state feedback and output feedback containment control protocols are proposed via a novel low-gain feedback approach. Consequently, the authors show that, under the assumption that the switching networks are jointly connected, semi-global state feedback and output feedback containment control of the multi-agent system can be attained. The effectiveness of the proposed algorithms is illustrated via numerical examples. © 2015 The Institution of Engineering and Technology.

关键词： Multi agent systems

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Posture estimation and human support using wearable sensors and walking-aid robot

Posture estimation and human support using wearable sensors ...

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作者： Huang, Jian Xu, Wenxia Mohammed, Samer Shu, Zhen Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Luoyu Road No. 1037 Wuhan China France

In this paper, an omni-directional walking-aid robot is developed to assist the elderly in the daily living movements. A motion control strategy of walking-aid robot based on the observation of the human status through wearable sensors is proposed. During normal walking, the robot is controlled using a conventional admittance control scheme. When the tendency of a fall is detected, the robot will immediately react to prevent the user from falling down. The distance between the human Center of Pressure (COP) and the midpoint of the human feet is assumed to be a significant feature to detecting the fall events. When the user is in a quasi-static state or walking slowly, the COP can be approximated by the projection of Center of Gravity (COG) of the user's body. A simple and low-cost wearable sensor system is proposed to measure online the COG of the user. A limitation of the proposed wearable sensor system is that the Head-Arms-Torso (HAT) of the user is assumed to be always in upright position, which may generate measurement error. From comparison experiments with a reference optical system it is found that the measurement error is acceptable especially at the early stage of fall event. Dubois possibility theory is applied to describe the membership function of "normal walking" state. A threshold based fall detection approach is obtained from online evaluation of the walking status. Finally, experiments demonstrate the validity of the proposed strategy. © 2014 Elsevier B.V. All rights reserved.

关键词： Wearable sensors

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OUGENE： a disease associated over-expressed and under-expressed gene database

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Science Bulletin 2016年第10期61卷 752-754页

作者： Xiaoyong Pan Hong-Bin Shen Section for Animal Genetics Bioinformatics and Breeding Center for Non-Coding RNA in Technology and Health University of Copenhagen 1870 Frederiksberg Denmark Department of Disease Systems Biology Novo NordiskFoundation Center for Protein Research University ofCopenhagen 1870 Frederiksberg Denmark Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

Gene over-expression or under-expression is closely associated with human diseases, which contributes to phenotypic variations and diversity. To our best knowledge, there is no single open specific resource available to provide the association information between gene over- or under-expression and various diseases. In this study, we presented a comprehensive disease-associated over- and under-expressed gene database （OUGene） based on our proposed text mining pipeline and several open curated databases. It contains total 41,269 unique associa- tions between 7,238 over- or under-expressed genes and 1,480 diseases, which are supported by 81,974 evidence sentences from 56,442 articles. The OUGene is compre- hensive and covers most important therapeutic areas. Meanwhile a new scoring system is designed to rank the associations based on benchmarking against hand-curated data. OUGene provides an easy-of-use web interface for researchers to analyze these data and visualize the associ- ated networks, which can give insights to the complex relationships between over- and under-expressed genes and diseases at a system level. It is available at ***. ***/bioinf/OUGene/.

关键词： Text mining Gene over- and under-expression Disease Database

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Aperiodic sampled-data sliding-mode control of fuzzy systems with communication delays via the event-triggered method

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IEEE Transactions on Fuzzy Systems 2016年第5期24卷 1048-1057页

作者： Wen, Shiping Huang, Tingwen Yu, Xinghuo Chen, Michael Z. Q. Zeng, Zhigang School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China Texas A and M University at Qatar Doha23874 Qatar Platform Technologies Research Institute RMIT University MelbourneVIC3001 Australia Department of Mechanical Engineering University of Hong Kong Hong Kong

This paper studies the aperiodic sampled-data control for the sliding-mode control (SMC) scheme of fuzzy systems with communication-induced delays via the event-triggered method. In practice, it is impossible to update control in continuous manner;thus, an event-based control technique has become popular with the advantage that the control task is executed only if it is triggered by an event. In this paper, the event-based sliding-mode control (ESMC) is designed for each linear subsystem of the global fuzzy model first. Then, the conditions for "fuzzily" amalgamated ESMC are discussed to stabilize the global fuzzy model. This ensures that the SMCis executed only when necessary. Furthermore, the results are extended to the fuzzy systems with communication-induced delays. Finally, case studies are carried out to demonstrate the effectiveness of the derived results. © 2015 IEEE.

关键词： Fuzzy systems

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Multistability of Recurrent Neural Networks with Nonmonotonic Activation Functions and Mixed Time Delays

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2016年第4期46卷 512-523页

作者： Liu, Peng Zeng, Zhigang Wang, Jun School of Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong

This paper presents new theoretical results on the multistability analysis of a class of recurrent neural networks with nonmonotonic activation functions and mixed time delays. Several sufficient conditions are derived for ascertaining the existence of 3n equilibrium points and the exponential stability of 2n equilibrium points via state space partition by using the geometrical properties of activation functions and algebraic properties of nonsingular M-matrix. Compared with existing results, the conditions herein are much more computable with one order less linear matrix inequalities. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of the 2n equilibrium points can be larger than their originally partitioned subspaces. Three numerical examples are elaborated with typical nonmonotonic activation functions to substantiate the efficacy and characteristics of the theoretical results. © 2015 IEEE.

关键词： Recurrent neural networks

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Patch-based Object Tracking via Locality-constrained Linear Coding

Patch-based Object Tracking via Locality-constrained Linear ...

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第35届中国控制会议

作者： Kunqi Gu Mingna Liu Tao Zhou Fanghui Liu Xiangjian He Jie Yang Yu Qiao Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai Institute of Spaceflight Control Technology Infrared Detection Technology Research and Development Center China Aerospace Science and Technology Corporation School of Computing and Communications University of Technology The Key Laboratory of Ministry of Education for System Control and Information Processing

ISBN: (纸本)9781509009107

In this paper,the Locality-constrained Linear Coding(LLC) algorithm is incorporated into the object tracking ***,we extract local patches within a candidate and then utilize the LLC algorithm to encode these *** on these codes,we exploit pyramid max pooling strategy to generate a richer feature *** feature histogram which integrates holistic and part-based features can be more discriminative and ***,an occlusion handling strategy is utilized to make our tracker more ***,an efficient graph-based manifold ranking algorithm is exploited to capture the relevance between target templates and *** tracking,target templates are taken as labeled nodes while target candidates are taken as unlabeled nodes,and the goal of tracking is to search for the candidate that is the most relevant to existing labeled nodes by manifold ranking *** on challenging video sequences have demonstrated the superior accuracy and robustness of the proposed method in comparison to other state-of-the-art baselines.

关键词： object tracking LLC pyramid max-pooling local appearance model manifold ranking

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Person re-identification with density-distance unsupervised salience learning 8th

Person re-identification with density-distance unsupervised ...

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8th International Conference on image and Graphics, ICIG 2015

作者： Zhou, Baoliang Zheng, Aihua Jiang, Bo Li, Chenglong Tang, Jin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology AnHui University Hefei China Key Laboratory of Industry Image Processing and Analysis in Anhui Province Hefei China

ISBN: (纸本)9783319219684

Human salience of pedestrians images is distinctive and has been shown importantly in person re-identification (or pedestrians identification) problem. Thus, how to obtain the salient area of pedestrian images is important for this salience based pedestrians identification problem. In this paper, we first show that this kind of salient area detection can be formulated as a kind of outlier detection problem, and then propose a novel unsupervised salience learning method using a local outlier-detection technique for person re-identification task. The main feature of the proposed salience computation method is that it exploits both distance and density information simultaneously. Experimental results on several datasets show the effectiveness of the proposed salience based person re-identification method. © Springer International Publishing Switzerland 2015.

关键词： Statistics

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Two Novel Cellular Neural Networks Based on Mem-elements

Two Novel Cellular Neural Networks Based on Mem-elements

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第三十四届中国控制会议

作者： SHEN Yi JIA Zhen Zhen WANG Xiao Ping LIU Yang School of Automation Huazhong University of Science and Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Research Institute of Huazhong University of Science and Technology in Shenzhen

ISBN: (纸本)9781467374439

Two types of novel cellular neural networks based on mem-elements are proposed, namely, MC-CNN and *** MC-CNN lets a memcapacitor replace the conventional linear capacitor of a cellular neural network cell. This improvement takes advantage of the nanoscale of memcapacitor and its natural nonlinearity, which makes the MC-CNN more compact and the output function simplified. Mathematical analysis of stability and simulation of image processing is presented to verify the feasibility and performance of MC-CNN. The EM-CNN is an economical improvement of the memristor synapse cellular neural network. In the EM-CNN, based on the symmetry of CNN templates, the amount of memristors and voltage-controlled current source is largely reduced. Thus, the EM-CNN is not only economical on the fabricating cost of CNN but also possesses a simpler cell structure which is beneficial to better implementation of CNN.

关键词： Cellular Neural Network,Memcapacitor,Memristor,image processing

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Two novel cellular neural networks based on mem-elements 34

Two novel cellular neural networks based on mem-elements

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34th Chinese control Conference, CCC 2015

作者： Shen, Yi Zhenzhen, Jia Xiaoping, Wang Yang, Liu School of Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Wuhan China Research Institute of Huazhong University of Science and Technology in Shenzhen Shenzhen China

ISBN: (纸本)9789881563897

Two types of novel cellular neural networks based on mem-elements are proposed, namely, MC-CNN and EM-CNN. The MC-CNN lets a memcapacitor replace the conventional linear capacitor of a cellular neural network cell. This improvement takes advantage of the nanoscale of memcapacitor and its natural nonlinearity, which makes the MC-CNN more compact and the output function simplified. Mathematical analysis of stability and simulation of image processing is presented to verify the feasibility and performance of MC-CNN. The EM-CNN is an economical improvement of the memristor synapse cellular neural network. In the EM-CNN, based on the symmetry of CNN templates, the amount of memristors and voltage-controlled current source is largely reduced. Thus, the EM-CNN is not only economical on the fabricating cost of CNN but also possesses a simpler cell structure which is beneficial to better implementation of CNN. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Cellular Neural Network image processing Memcapacitor Memristor

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