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作者： Cen, Lihui Xi, Yugeng Li, Dewei Cen, Yigang Department of Control Engineering Central South University Changsha Hunan Province China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Department of Automation Shanghai Jiaotong University Shanghai200240 China School of Computer and Information Technology Beijing Jiaotong University Beijing China

This paper proposes a boundary feedback control design for open canal networks using the linearization of boundary conditions. For open canal networks with any types of cross-sections, which can be modelled by the Saint-Venant equations, the characteristic form in terms of Riemann invariants has been established. Under this established characteristic form, the stabilizing boundary control law has been developed by linearizing the boundary conditions for both a single reach and the open-channel network composed by multi-reaches in a cascade. The design of the boundary feedback control laws for both a single canal and the cascaded networks is illustrated in a unified framework, which extends the results in the literature. © The Author(s) 2014.

关键词： Boundary conditions

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A generalized piecewise quadratic lyapunov function approach to estimating the domain of attraction of a saturated system

A generalized piecewise quadratic lyapunov function approach...

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1st IFAC Conference on Modelling, Identification and control of Nonlinear systems, MICNON 2015

作者： Li, Yuanlong Lin, Zongli Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA229044743 United States

This paper revisits the problem of estimating the domain of attraction of a saturated system with an algebraic loop. A piecewise quadratic Lyapunov function of an augmented state vector composing of the system state and the saturated input has been proposed for use in estimating the domain of attraction for a saturated system. Considering the relationship between the system states and the saturation function, we propose in this paper a generalized piecewise quadratic Lyapunov function, which results from adding a term that characterizes the regional sector condition of the saturated input to the piecewise quadratic Lypunov function. The matrix associated with the generalized piecewise quadratic Lyapunov function is not required to be positive definite, and thus a set of less conservative stability conditions are established, from which a larger estimate of the domain of attraction can be obtained. Simulation results indicate that the effectiveness and superiority of the proposed method.

关键词： Lyapunov functions

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SOCIAL LEARNING WITH TIME-VARYING WEIGHTS

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Journal of systems Science & Complexity 2014年第3期27卷 581-593页

作者： LIU Qipeng FANG Aili WANG Lin WANG Xiaofan Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

This paper investigates a non-Bayesian social learning model, in which each individual updates her beliefs based on private signals as well as her neighbors＇ beliefs. The private signM is involved in the updating process through Bayes＇ rule, and the neighbors＇ beliefs are embodied in through a weighted average form, where the weights are time-varying. The authors prove that agents eventually have correct forecasts for upcoming signals, and all the beliefs of agents reach a consensus. In addition, if there exists no state that is observationally equivalent to the true state from the point of view of all agents, the authors show that the consensus belief of the whole group eventually reflects the true state.

关键词： Consensus social learning social networks time-varying weights.

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Locally linear representation manifolds margin 11th

Locally linear representation manifolds margin

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11th International Conference on Intelligent Computing, ICIC 2015

作者： Li, Bo Wang, Yun-Qing Lei, Lei Fan, Zhang-Tao School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (纸本)9783319221793

In this paper, a novel supervised multiple manifolds learning method is presented for dimensionality reduction, which is titled locally linear representation manifold margin (LLRMM). In the proposed LLRMM, both an inter-manifold graph and intra-manifold graph are constructed, where any point in the inter-manifold graph must select neighbors from other manifolds while the neighborhood in the intra-manifold graph are composed of samples from the same manifold. Then the least locally linear representation technique is introduced to optimize the reconstruction weights as well as the corresponding inter-manifold scatter and intra-manifold scatter, based on which manifolds margin can be reasoned. At last, a discriminant subspace is explored. Experiments on some benchmark face data sets have been conducted and experimental results show that the proposed method outperforms some related state-of-the-art dimensionality reduction methods. © Springer International Publishing Switzerland 2015.

关键词： Computers

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A new microcalcification detection method in full field digital mammogram images 11th

A new microcalcification detection method in full field digi...

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11th International Conference on Intelligent Computing, ICIC 2015

作者： Liu, Xiaoming Mei, Ming Sun, Weiwei Liu, Jun College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing Real-time Industrial System Wuhan China

ISBN: (纸本)9783319221793

Breast cancer is a great threat for women around the world. Mammography is the main approach for early detection and diagnosis. Microcalcification (MC) in mammograms is one of the important early signs of breast cancer. Their accurate detection is important in computer-aided detection (CADe). In this paper, we proposed a new Microcalcification detection method for full field digital mammograms (FFDM) by integrating Possibilistic Fuzzy c-Means (PFCM) clustering algorithm and weighted support vector machine (WSVM). The method includes a training process and a testing process. In the training process, possible microcalcification regions are located and extracted. Extracted features are selected with mutual information based technique. Positive and negative samples are weighted with PFCM and used to train a weighted SVM. A similar procedure is performed on test images. The proposed method is evaluated on a database of 410 clinical mammograms and compared with a standard unweighted support vector machine classifier. © Springer International Publishing Switzerland 2015.

关键词： Mammography

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Utilizing Fullerenols as Surfactant for Carbon Nanotubes Dispersions Preparation

Journal of Materials

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Journal of Materials 2017年第1期2017卷

作者： Jianlong Ji Chang Qiao Yali Liu Wendong Zhang Shengbo Sang Xing Yang Aoqun Jian Qianqian Duan Qiang Zhang Ying Liu Micro Nano System Research Center Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education College of Information Engineering Taiyuan University of Technology Taiyuan 030024 *** Advanced Coal Mine Machinery and Equipment Collaborative Innovation Center of Shanxi Province College of Information Engineering Taiyuan University of Technology Taiyuan 030024 *** MEMS Laboratory Department of Precision Instruments and Mechanology Tsinghua University Beijing 100084 *** College of Materials Science and Engineering Taiyuan University of Technology Taiyuan 030024 ***

Dispersions of individual carbon nanotubes (CNTs) are crucial for nanodevices and polymer/CNTs nanocomposites. In this paper, stable and homogenous dispersions of individual multiwalled carbon nanotubes (MWCNTs) have been synthesized. The factors influencing the dispersibility mechanism, including the surfactant concentration and the pH value, have been investigated. SEM images display the impurities sticking on MWCNTs which have been removed. The oxygen-containing groups on the surface of MWCNTs sample have been detected through FT-IR and Raman spectra. All experimental results illustrate that using fullerenols as surfactant can greatly improve the dispersibility of MWCNTs. Moreover, the prepared dispersions exhibit good stability that the sediment percentage of fullerenols-MWCNTs is only 5.2% after 5 days.

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Data-Based Health State Analysis for the Axle of High Speed Train

Data-Based Health State Analysis for the Axle of High Speed ...

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International Conference on Computational Intelligence and Security

作者： Guo Xie Minying Ye Xinhong Hei Jinwei Zhao Fucai Qian Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

Taking into account that the present popular methods, such as the judgement of the axle failure based on temperature threshold, and the early warning of axle based on real-time temperature analysis, cannot analyze the changing of performance trends, a health state analysis method for the axle of high-speed train based on long-term temperature monitoring data is proposed in this paper, which including the following main steps: (1) Preprocessing of the original data to correct the singular zero value and complement the missing values, (2) Smoothing of the processed data in order to automatically extract the beginning and end points of every temperature rising stage of axles, (3) Establishment of the calculation method of temperature rising rate, and evaluating the health sate of axles based on the temperature rising rate. Finally, the proposed method is validated based on the data from a test line, the results demonstrate the effectiveness and practicability of the method.

关键词： Axles Temperature distribution Aging Safety Data mining Fault diagnosis Monitoring

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Idea creation of creative computing based on embedding features and ontology 2016

Idea creation of creative computing based on embedding featu...

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3rd Multidisciplinary International Social Networks Conference, MISNC 2016, 5th ASE International Conference on Social Informatics, SocialInformatics 2016 and 7th ASE International Conference on Data Science, DS 2016

作者： Zhang, Fuquan Mao, Zijing Ding, Gangyi Zhang, Rui Lai, Junjiang School of software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Ji Yuan Ju Yuan Jin Shan Fuzhou Fujian350121 China Department of Electrical Engineering University of Texas at San Antonio One UTSA Circle San AntonioTX78249 United States Software Building Beijing Institute of Technology 5 South Zhongguancun Street Haidian Beijing100081 China Department of Mathematics Minjiang University Fuzhou No.150 Binzhou Road Jin Shan Fuzhou Fujian350108 China

ISBN: (纸本)9781450341295

This paper used clustering to embed features and use ontology to simulate the process of idea creation from human brain. All the technologies are applied on the frame of creative computing. We are try to display the emergence, the self-organization, the self-coordination of idea creation process of human brain. By creative computing we will try to discover how the idea coming from step by step. From this paper, you will see the process in five steps from blurry motivation to clear creative idea. © 2016 ACM.

关键词： Ontology

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Moving target detection in the cepstrum domain for passive coherent location(PCL) radar

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Frontiers of information Technology & Electronic Engineering 2015年第9期16卷 785-795页

作者： Ji-chuan LI Xiao-de LU Hui ZHANG Peng-cheng YANG Yu LIU Mao-sheng XIANG Science and Technology on Microwave Imaging Laboratory Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of ElectronicsChinese Academy of Sciences

A cepstrum moving target detection （CEPMTD） algorithm based on cepstrum techniques is proposed for passive coherent location （PCL） radar systems. The primary cepstrum techniques are of great success in recognizing the arrival times of static target echoes. To estimate the Doppler frequencies of moving targets, we divide the radar data into a large number of seg- ments, and reformat these segments into a detection matrix. Applying the cepstrum and the Fourier transform to the fast and slow time dimensions respectively, we can obtain the range information and Doppler information of the moving targets. Based on the CEPMTD outlined above, an improved CEPMTD algorithm is proposed to improve the detection performance. Theoretical analyses show that only the target＇s peak can be coherently added. The performance of the improved CEPMTD is initially vali- dated by simulations, and then by experiments. The simulation results show that the detection performance of the improved CEPMTD algorithm is 13.3 dB better than that of the CEPMTD algorithm and 6.4 dB better than that of the classical detection algorithm based on the radar cross ambiguity function （CAF）. The experiment results show that the detection performance of the improved CEPMTD algorithm is 1.63 dB better than that of the radar CAF.

关键词： Moving target detection Cepstrum techniques Cross ambiguity fimction （CAF） Passive coherent location （PCL）radar

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Distributed Cooperative Coverage of Mobile Robots with Consensus-Based Connectivity Estimation

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Journal of Shanghai Jiaotong university(Science) 2014年第3期19卷 279-286页

作者：李晓丽赵曙光刘浩 School of Information Science and Technology Donghua University Key Laboratory of System Control and Information Processing of Ministry of Education

This paper deals with the discrete-time connected coverage problem with the constraint that only local information can be utilized for each robot. In such distributed framework, global connectivity characterized by the second smallest eigenvalue of topology Laplacian is estimated through introducing distributed minimal-time consensus algorithm and power iteration algorithm. A self-deployment algorithm is developed to disperse the robots with the precondition that the estimated second smallest eigenvalue is positive at each time-step. Since thus connectivity constraint does not impose to preserve some certain edges, the self-deployment strategy developed in this paper reserves a sufficient degree of freedom for the motion of robots. Theoretical analysis demonstrates that each pair of neighbor robots can finally reach the largest objective distance from each other while the group keeps connected all the time, which is also shown by simulations.

关键词： coverage distributed cooperative control minimal-time consensus eigenvalue estimation

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