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Chinese Automation Congress (CAC)

作者： Jin Qian Jian Huang Songhyok Ri Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China

In this paper, an adaptive fuzzy sliding mode control approach which combines fuzzy control with the sliding mode control, is applied for the tracking control of pneumatic muscle actuator (PMA). This actuator is widely used in the rehabilitation robots while hard to control due to its strong nonlinearity. The switching-type control term in the sliding mode control law is approximated by a fuzzy system. Based on Lyapunov theory, the stability of the closed-loop PMA system can be guaranteed. Both simulation and experimental studies were carried out to verify the proposed methods. The experiments were conducted on a real PMA system, which was connected with the xPC target system. The results demonstrate the validity of the PMA as well as the effectiveness of the control algorithm even there exist system uncertainties and external bounded disturbances.

关键词： Software Real-time systems Fuzzy control Robots Switches Mathematical model Sliding mode control

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Mid-level parts mined by feature selection for action recognition

Mid-level parts mined by feature selection for action recogn...

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Asian Conference on Pattern Recognition (ACPR)

作者： ShiWei Zhang Nong Sang ChangXin Gao FeiFei Chen Jing Hu Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology China

ISBN: (纸本)9781479961016

This paper develops a method to learn very few discriminative part detectors from training videos directly, for action recognition. We hold the opinion that being discriminative to action classification is of primary importance in selecting part detectors, not just intuitive. For this purpose, part selection based on feature selection is proposed, employing SVM method. Firstly, large number of candidate detectors are trained using k-means and Exemplar-LDA techniques in whitened feature space. Secondly, each candidate part detector is regarded as a visual feature, so that detector selection can be achieved by feature selection. Detectors with larger weight, indicating more discriminative, will be selected. Meanwhile, to keep space-volume structure information, we use the novel method saliency-driven pooling to form feature primitives which are concatenated into mid-level feature vector. Finally, we conduct experiments on three challenging action datasets (KTH, Olympic Sports, HMDB51) and the results outperform the state-of-the-art.

关键词： Detectors Feature extraction Videos Support vector machines Semantics Pattern recognition image recognition

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An efficient MRF embedded level set method for image segmentation

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IEEE Transactions on image processing 2015年第1期24卷 9-21页

作者： Yang, Xi Gao, Xinbo Tao, Dacheng Li, Xuelong Li, Jie State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an710071 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 235 Jones Street UltimoNSW2007 Australia State Key Laboratory of Transient Optics and Photonics Xi'An Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an710119 China Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an710071 China

This paper presents a fast and robust level set method for image segmentation. To enhance the robustness against noise, we embed a Markov random field (MRF) energy function to the conventional level set energy function. This MRF energy function builds the correlation of a pixel with its neighbors and encourages them to fall into the same region. To obtain a fast implementation of the MRF embedded level set model, we explore algebraic multigrid (AMG) and sparse field method (SFM) to increase the time step and decrease the computation domain, respectively. Both AMG and SFM can be conducted in a parallel fashion, which facilitates the processing of our method for big image databases. By comparing the proposed fast and robust level set method with the standard level set method and its popular variants on noisy synthetic images, synthetic aperture radar (SAR) images, medical images, and natural images, we comprehensively demonstrate the new method is robust against various kinds of noises. In particular, the new level set method can segment an image of size 500 x 500 within 3 s on MATLAB R2010b installed in a computer with 3.30-GHz CPU and 4-GB memory. © 2014 IEEE.

关键词： image segmentation

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controllable deoxyribonucleic acids sub-tile self-assembly by deoxyribonucleic acids strand displacement

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Journal of Computational and Theoretical Nanoscience 2015年第10期12卷 3774-3780页

作者： Wang, Yanfeng Zhao, Taotao Shi, Xiaolong Li, Mengmeng Cui, Guangzhao School of Electrical and Information Engineering Henan Key Lab of Information-Based Electrical Appliances Zhengzhou University of Light Industry Zhengzhou China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan China

Here we report a controllable four DNA sub-tiles, self-assembling into 4-arm DNA tiles, under control of a DNA strand displacement based on DNA sequential circuit. The motif is encoded, compiled and simulated successively in Visual DSD software. The simulation results show that the four kinds of sub-tiles in the motif combine to their neighbors one after another with a certain time delay and finally form into 4-arm DNA tiles. The formation of the 4th arm of a 4-arm DNA tile indicates that all the 4-arm DNA tiles have been assembled, which implies high productivity of the 4-arm DNA tiles. We also analyze the time responses of the DNA sequence circuit by adjusting the concentration proportions of reactants and/or ordering bind and unbind rates of toeholds in simulation. These simulation results demonstrate that high concentration proportions of reactants and/or toeholds reacting at ascending order rates can shorten the time response more sharply than that low concentration proportion of reactants and/or in a descending order. The motif furthers the integration for DNA sub-tile self-assembly and DNA strand displacement. Copyright © 2015 American Scientific Publishers.

关键词： DNA

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RETRACTED: Dual-mode predictive flexible rotor control for active magnetic bearings with input constraints

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Journal of Vibration and control 2016年第20期23卷 NP2页

作者： Yue Wu Jie Zhao Hai-Tao Zhang Ming-Can Fan Xi Yu Guangdong HUST Industrial Technology Research Institute Guangdong Province Key Lab of Digital Manufacturing Equipment ChinaKey Laboratory of Image Processing and Intelligent Control School of Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology China Key Laboratory of Image Processing and Intelligent Control School of Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology China Department of Mathematics Huizhou University China School of Electrical and Information Engineering Xi'an Technology University China

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A novel method to derive ambulatory blood pressure from the radial pressure waveform

Communications in Computer and Information Science

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Communications in Computer and information Science 2014年 472卷 176-181页

作者： He, Long Chen, Zhihua Zhang, Zheng Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)9783662450482

In this paper, we develop a novel application of independent component analysis (ICA) based auto-regression forecasting model(ICAARF). The method can noninvasively, continuously and conveniently derive ambulatory blood pressure (ABP) from the radial artery pressure waveform (RAPWF). To eliminate the effect of correlative factors in measurement, the ICA method is used to decomposite the raw signal and extract the independent component affected by blood pressure (BP). Based on the spectrum density of independent component, an auto-regression forecasting model is set up to derive BP. Experimental results show an excellent correlation and agreement with the BP measured by Omron electronic BP monitor (Type: HEM-7012). If the ICA-ARF is used, the the error can be reduced from 7.4mmHg to 2.55mmHg. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Blood pressure

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Cell resistance slope combined with LVQ neural network for prediction of anode effect 6

Cell resistance slope combined with LVQ neural network for p...

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6th International Conference on intelligent control and information processing, ICICIP 2015

作者： Zhou, Kaibo Lin, Zhikai Yu, Dengzhi Cao, Bin Wang, Ziqian Guo, Sihai School of Automation Huazhong University of Science and Technology Key Laboratory of Ministry of Education Image Processing and Intelligent Control Wuhan430074 China Guiyang Aluminum Magnesium Design and Research Institute Guiyang550004 China School of Automation Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781479917174

It is an important part in aluminum electrolysis production to control the anode effect (AE). Since there are some shortcomings in traditional methods of anode effect prediction in aluminum electrolysis, this paper combined two methods, the slope of cell resistance and learning vector quantization (LVQ) neural network, to predict anode effect. First of all, the first prediction of anode effect will be conducted based on the slope of cell resistance. Afterwards, the inaccurate data are supposed to be re-predicted. The second prediction consists of two steps, one is to estimate the power spectrum from the signal of cell resistance by means of periodogram, the other is to re-predict the anode effect with the LVQ neural network, since the energy of frequency bands are served as the input feature variables of neural network, so as to raise the accuracy of prediction. It turned out that the success rate of ten-minute in advance prediction for anode effect can be above 85%, though just cell resistance signal is studied. © 2015 IEEE.

关键词： Forecasting

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A new automatic mass detection method for breast cancer with false positive reduction

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Neurocomputing 2015年 152卷 388-402页

作者： Xiaoming Liu Zhigang Zeng School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430081 China

Mass localization is a crucial problem in computer-aided detection (CAD) system for the diagnosis of suspicious regions in mammograms. In this paper, a new automatic mass detection method for breast cancer in mammographic images is proposed. Firstly, suspicious regions are located with an adaptive region growing method, named multiple concentric layers (MCL) approach. Prior knowledge is utilized by tuning parameters with training data set during the MCL step. Then, the initial regions are further refined with narrow band based active contour (NBAC), which can improve the segmentation accuracy of masses. Texture features and geometry features are extracted from the regions of interest (ROI) containing the segmented suspicious regions and the boundaries of the segmentation. The texture features are computed from gray level co-occurrence matrix (GLCM) and completed local binary pattern (CLBP). Finally, the ROIs are classified by means of support vector machine (SVM), with supervision provided by the radiologist׳s diagnosis. To deal with the imbalance problem regarding the number of non-masses and masses, supersampling and downsampling are incorporated. The method was evaluated on a dataset with 429 craniocaudal (CC) view images, containing 504 masses. Among them, 219 images containing 260 masses are used to optimize the parameters during MCL step, and are used to train SVM. The remaining 210 images (with 244 masses) are used to test the performance. Masses are detected with 82.4% sensitivity with 5.3 false positives per image (FPsI) with MCL, and after active contour refinement, feature analysis and classification, it obtained 1.48 FPsI at the sensitivity 78.2%. Testing on 164 normal mammographic images showed 5.18 FPsI with MCL and 1.51 FPsI after classification. Experiments on mediolateral oblique (MLO) images have also been performed, the proposed method achieved a sensitivity 75.6% at 1.38 FPsI. The method is also analyzed with free response operating characteristi

关键词： Mass detection Breast cancer Level set Local binary pattern Support vector machine

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Observer-Based Robust Coordinated Tracking of Multi-Agent Systems with Input Saturation

Observer-Based Robust Coordinated Tracking of Multi-Agent Sy...

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IEEE Annual Conference on Decision and control

作者： Xiaoling Wang Housheng Su Xiaofan Wang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781479978878

This paper addresses the robust semi-global coordinated tracking problem of multiple-input multiple-output (MIMO) multi-agent systems with input saturation and communication noise. A distributed observer-based coordinated tracking protocol is constructed by combining a novel parameterized low-and-high feedback technique with the high-gain observers design approach. It is shown that, under the assumptions that each agent is asymptotically null-controllable with bounded controls and the network is connected, semi-global consensus tracking or semi-global swarm tracking can be attained for left-invertible and minimal-phase systems.

关键词： noise(communication) bounded control tracking high gain Agents

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Impulsive positive observers and dynamic output feedback stabilization of positive linear continuous systems

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International Journal of Robust and Nonlinear control 2016年第13期27卷

作者： Jiang-Wen Xiao Meng-Jie Hu Yan-Wu Wang Wu-Hua Chen School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China College of Mathematics and Information Science Guangxi University Nanning 530004 China

This paper is concerned with the design and the synthesis of the impulsive positive observer (IPO) for positive linear continuous systems. The IPO can estimate the states for positive systems even when the measured output is only available at discrete-time instants. In this paper, a time-varying weighted copositive Lyapunov function is constructed, and the upper and lower bounds of impulsive intervals method combined with the convex combination technique are used to establish sufficient conditions for the existence of the IPO. Furthermore, the design of the dynamic output feedback controller based on the IPO is addressed to positively stabilize positive linear systems. Algorithms are given to design the IPO and the controller, respectively. Finally, two numerical examples are provided to show the effectiveness of the theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： impulsive positive observer dynamic output feedback controller time-varying weighted copositive Lyapunov function positive system upper and lower bounds of impulsive intervals method convex combination technique

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