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Multiple neural networks switched prediction for landslide displacement

Engineering Geology 2014年 186卷 91-99页

作者： Lian, Cheng Zeng, Zhigang Yao, Wei Tang, Huiming 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 School of Computer Science South-Central University for Nationalities Wuhan 430074 China Faculty of Engineering China University of Geosciences Wuhan 430074 China

An accurate prediction of landslide displacement is challenging and of great interest to governments and researchers. In order to reduce the risk of selecting the types of influencing factors and artificial neural networks (ANNs), a multiple ANNs switched prediction method is proposed for landslide displacement forecasting. In the first stage, a set of individual neural networks are developed based on different environmental factors and/or different training algorithms. In the second stage, a switched prediction method is used to select the appropriate individual neural network for prediction purpose. For verification and testing, three typical landslides in Three Gorges Reservoir, namely Baishuihe landslide, Bazimen landslide and Shiliushubao landslide, are presented to test the effectiveness of our method. Application results demonstrate that the proposed method can significantly improve model generalization and perform similarly to, or better than, the best individual ANN predictor. © 2014 Elsevier B.V.

关键词： Forecasting

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A novel ANN-based harmonic extraction method tested with ESN, RNN and MLP in shunt active power filters

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International Journal of Wireless and Mobile Computing 2014年第2期7卷 123-131页

作者： Xu, Jinbang Yang, Jun Shen, Anwen Chen, Junfeng Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

With the wide use of power conversion devices - 'nonlinear loads' - many harmonic currents are being injected into the power grid. Shunt Active Power Filters (SAPF) are the power electronic equipment to compensate the harmonic currents caused by nonlinear loads. As the foundation of the harmonics recognition and compensation, harmonic extraction is the key technology in SAPF. Artificial Neural Networks (ANN) method has the features of parallel computation and satisfactory results for distorted source voltages over traditional extraction methods. This paper proposes a new harmonic extraction method based on ANN. To test the feasibility of different types of neural networks in this application, this paper compares the performances of three types of ANN: Echo State Networks (ESN), Recurrent Neural Networks (RNN) and Multilayer Perceptron Networks (MLP). © 2014 Inderscience Enterprises Ltd.

关键词： Extraction

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control reconfiguration on deadlocked gimballed thrust of launch vehicle

Lecture Notes in Control and Information Sciences

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Lecture Notes in control and Information Sciences 2014年 452卷 27-59页

作者： Liu, Lei Wang, Yongji Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9783642363849

An unprecedented challenge of the new generation launch vehicle control is its four parallel strap-on engines are oscillateable by the servomechanism. It increases the manoeuvrability of the vehicle and the control complexity simultaneously. The chapter investigates actuator failure compensation for new generation launch vehicle control. A control reconfiguration scheme of fault-tolerant control is developed to enhance the reliability of launch vehicle attitude control systems and prevent the control invalidation caused by the deadlock of the oscillating actuator, based on the congruity of the composite moment before and after the failure happens. This reconfiguration scheme is capable of utilizing the remaining control authority to achieve the desired performance in the presence of deadlock at certain detectable angle occurring in one or several actuators at unknown time instants. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Launch vehicles

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Implementation of Memristive Neural Networks with Spike-rate-dependent Plasticity Synapses

Implementation of Memristive Neural Networks with Spike-rate...

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International Joint Conference on Neural Networks

作者： Yide Zhang Zhigang Zeng Shiping Wen School of Automation Huazhong University of Science and Technology and Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China

ISBN: (纸本)9781479914821

The property of changing resistance according to applied currents of memristors makes them candidates for emulating synapses in artificial neural networks. In this paper, we introduce a memristive synapse design into neural network circuits. Combined with modified integrate-and-fire (I&F) complementary metal-oxide-semiconducter (CMOS) neurons, the memristive neural network shows similarities to its biological counterpart, in respect of biologically realistic, current-controlled spikes and adaptive synaptic plasticity. Then, the spike-rate-dependent plasticity (SRDP) of the synapse, an extended protocol of the Hebbian learning rule, is originally implemented by the circuit. And some advanced neural activities including learning, associative memory and forgetting are realized based on the SRDP rule. These activities are comprehensively validated on a neural network circuit inspired by famous Pavlov's dog-experiment with simulations and quantitative analyses.

关键词： Neurons Memristors Biological neural networks Biological system modeling Protocols Semiconductor device modeling Integrated circuit modeling

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Connectivity Exploration after Stroke with Structural Equation Modeling

Connectivity Exploration after Stroke with Structural Equati...

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2012 Third International Conference on Theoretical and Mathematical Foundations of Computer Science(ICTMF 2012)

作者： Wei Li Hongtao Tan Xiaojun Wang Zhiqiao Yan Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of ChinaHuazhong University of Science and Technology

Neuroplasticity has been demonstrated to play an important role in function recovery *** this paper,stroke patients and controls were subjected to functional magnetic resonance imaging(fMRI) study for *** group independent componentanalysis was used to get the time courses of the interested regions in *** investigate the reorganization of cerebral cortex after stroke,Structural Equation Modeling(SEM) was applied to construct a locomotor brain network *** results were analyzed to investigate thebrain activity changes involved in the cerebral motor cortex circuitry aroused by the hand *** contrast to healthy people,we found that the brain activity changes of the stroke patientscould not onlyshow the local changes around injured regions,but also the global transformation of brain related to *** the differences were examined in terms of changes in path coefficients between brain regions.

关键词： fMRI,ICA,SEM,Stroke,Neuroplasticity

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A research on human cognitive modeling in rumor spreading based on HTM

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 461卷 268-277页

作者： Li, Xiangchen Chen, X. Wang, Wei School of Automation Huazhong University of Science and Technology Wuhan China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan China

ISBN: (纸本)9783662452820

As a sociological phenomenon, rumor spreading has been widely researched by sociologists and other fields’ scholars. How do people generate those strange thinking about the rumor? This paper, from artificial intelligence view, focuses on an algorithm based on Hierarchical Temporal Memory (HTM) to simulate human cognitive process of generating rumors from individual heterogeneous living experience. Comparison with classical Bayesian Networks, our algorithm could effectively and really simulate human cognitive process of rumors, and in accordance with some typical psychology effects proved by sociologists and psychologists. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Bayesian networks

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On the periodic dynamics of memristor-based neural networks with time-varying delays

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Information Sciences 2014年 279卷 358-373页

作者： Jiejie Chen Zhigang Zeng Ping Jiang School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan 430074 China

In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valued analysis, differential inclusions theory and a new Lyapunov function method, we prove that the neural network has a unique periodic solution, which is globally exponentially stable. Moreover, we prove the existence, uniqueness and global exponential stability of equilibrium point for time-varying delayed memristor-based neural networks with constant coefficients. The obtained results improve and extend previous works on memristor-based or usual neural network dynamical systems with continuous or discontinuous right-hand side. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results.

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Consensus of Edge Dynamics on Directed Multi-agent Systems

Consensus of Edge Dynamics on Directed Multi-agent Systems

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The 33th Chinese control Conference第33届中国控制会议

作者： Xiaofan Wang Xiaoling Wang Housheng Su Department of Automation Shanghai Jiaotong Universityand Key Laboratory of System Control and Infor School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry o

ISBN: (纸本)9781479947249

Consensus in multi-agent systems means that reach an agreement among states of the whole ***,almost all the existed works on consensus have been in the description of the states of nodes,and fewer efforts have been devoted to the consensus taking place on the edges of multi-agent *** this paper,we focus on the dynamics proceed on the edges and establish a discrete-time and a continuous-time edge consensus protocols respectively for directed multi-agent *** mapping the edge topology to its line graph of the original nodal topology,we analyze the consensus of the edge protocols rigorously,and get that both the discrete-time protocol and the continuous-time protocol of directed multi-agent systems can guarantee that an edge consensus is asymptotically reached for all initial states when the original directed system is strongly *** simulations are provided to show the effectiveness of both the discrete-time and the continuous-time models.

关键词： Consensus Edge Protocol Multi-agent Systems Line Graph

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Exponential synchronization of coupled memristive neural networks via pinning control

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Chinese Physics B 2013年第5期22卷 203-212页

作者：王冠沈轶尹泉 Department of Control Science and Engineering Huazhong University of Science and Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control

This paper is concerned with the exponential synchronization problem of coupled memristive neural networks. In contrast to general neural networks, memristive neural networks exhibit state-dependent switching behaviors due to the physical properties of memristors. Under a mild topology condition, it is proved that a small fraction of controlled sub- systems can efficiently synchronize the coupled systems. The pinned subsystems are identified via a search algorithm. Moreover, the information exchange network needs not to be undirected or strongly connected. Finally, two numerical simulations are performed to verify the usefulness and effectiveness of our results.

关键词： synchronization memristor coupled neural networks pinning control

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