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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Wang, Jin Gao, Changxin Hu, Jing Sang, Nong Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, we address the problem of person reidentification (re-id), which remains to be challenging due to view point changes, pose variations, different camera settings, etc. Different from common methods that concatenate descriptors extracted from different support regions and feature channels directly as a long vector, we encode the importance of different feature channels and support regions explicitly and propose a two-layer distance ensemble model called DeNet to measure the similarity between two images. The first layer of DeNet combines distances of different support regions while the second layer weights different feature channels. Weight parameters of DeNet are learnt under the large margin framework with the goal of maximizing the difference between distances of positive and negative matching pairs. Our method achieves very competitive results on the widely used VIPeR and PRID 450S datasets. © 2015 IEEE.

关键词： Computers

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A multi-agent coordinated planning approach for deadline required emergency response tasks

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IET control Theory and Applications 2015年第3期9卷 447-455页

作者： Zhou, Chao Wang, Hongwei Zhuo, Hankz Hankui Key Laboratory of Image Processing and Intelligent Control of Education Ministry Institute of Systems Engineering Huazhong University of Science and Technology Wuhan430074 China School of Advanced Computing SunYat-sen University Guangzhou510006 China

This study investigates the emergency decision-making problem in a multi-agent system. Departments are modeled as agents to perform coordinated planning to obtain a global action plan with a short execution time constrained by a prescribed deadline. A novel multi-agent planning approach is proposed to coordinate for the solution among agents in the system. The approach consists of two stages. For the first stage, a coordinated planning and scheduling method is designed to generate a candidate global action plan. In this plan, durative actions are assigned to proper time intervals with the consideration of temporal relationships among agents. For the second stage, a coordination mechanism based on local heuristics is proposed to reduce the global time cost of the candidate plan to satisfy the deadline. An experimental study of emergency evacuation problem is conducted to demonstrate the effectiveness and efficiency of the proposed approach. © 2015 The Institution of Engineering and Technology.

关键词： Multi agent systems

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Leg hybrid rehabilitation based on hip-knee exoskeleton and ankle motion induced by FES

Leg hybrid rehabilitation based on hip-knee exoskeleton and ...

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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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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 elab.rated 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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A novel method for the construction of evolutionary tree based on expectation maximization algorithm

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3799-3803页

作者： Chen, Zhihua Zhao, Yang Wang, Zhuo Kou, Zheng Li, Hanggao Key Lab. of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei430074 China Institute of Biomedical and Pharmaceutical Sciences College of Biological Engineering and Food Science Hubei University of Technology Wuhan Hubei430068 China College of Computer Science South-Central University for Nationalities Wuhan Hubei430074 China

The difference of protein sequence or protein structure can be used for the construction of molecular evolutionary tree or phytogenetic tree with certain hierarchy and topology. The divergent points in the tree suggest that new genes appeared or common ancestors varied. The lengths of the branch in the tree show the evolution distances between proteins when divergences happened. The analysis of protein evolution can propose some methods for molecular evolution of various species and can confirm the accurate status in the evolution history. Moreover, the molecular evolution tree of proteins is a strong evidence for species classification. In the paper, the trees are constructed by the regular express of protein sequences and the expectation maximization (EM) algorithm. The proposed method in the paper can be used conveniently and can give reliable results, which benefit the biology computing and sequence analysis. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Proteins

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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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