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2011 International Conference on Automation and Robotics, ICAR 2011

作者： Hong, Hanyu Zhang, Xiuhua Yang, Yijun Yu, Zhejun Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430205 China

ISBN: (纸本)9783642256455

Steel billet recognition is an urgent requirement in the steel industry of heavy rail line. Due to high temperature and complex scene in the rolling line, the recognition at the end of billet is quite different from optical character recognition with simple background and vehicle license plate recognition. In order to solve the problem, this paper presents some new schemes in character location, segmentation and recognition in the complex scene. These proposed algorithms include the location algorithm of multilevel filter based on separability criterion, the segmentation algorithm based on intelligent multi-agent and the recognition algorithm of character features matching combining the template matching. The results show that the proposed algorithms are effective for steel billet character recognition in the complex scene. © 2011 Springer-Verlag.

关键词： Template matching

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P systems with 2D picture grammars

P systems with 2D picture grammars

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6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011

作者： Song, Tao Zeng, Xiangxiang Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9780769545141

In formal language theory of two-dimensions, 2D picture grammars are powerful tools to generate picture languages. In this work, we incorporate the idea of membrane systems (also called P systems) into 2D picture grammars, thus introducing a new kind of picture language generating devices, named P systems with 2D picture grammars. Inspired by the structure and functioning of living cells, such a system has a hierarchical membrane structure, symbol array objects and evolution rules of 2D picture grammars. In each region delimited by the membrane structure, array objects can evolve in a parallel manner according to evolution rules present in the region, like the way biochemical objects evolve in living cells or organisms. The computational result of P system with 2D picture grammars is the set of pictures (rectangular arrays) present in a specific output membrane when the system halts. We obtain several comparison results, which show that with the membrane structure, the generating power of Siromoney matrix grammar, 2D contextfree grammar and basic puzzle grammar can be enlarged. © 2011 IEEE.

关键词： Membrane structures

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-Gain analysis of event-triggered networked control systems: a discontinuous Lyapunov functional approach

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International Journal of Robust and Nonlinear control 2012年第11期23卷

作者： Songlin Hu Dong Yue Department of Control Science and Engineering and the Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

In this paper, the problems of exponential stability and -gain analysis of event-triggered networked control systems (NCSs) with network-induced delays are studied. We first propose event-triggering conditions in the sensor side and controller side, respectively. Because the implementation of our event-triggering scheme only needs periodic supervision of the system state at the constant sampling instants, instead of being monitored continuously, it is expected that the scheme will improve the resource utilization. Taking the network-induced delays into account and using delay system approach, we constructed a unified model of NCSs with hybrid event-triggering schemes. On the basis of this model, sufficient conditions for the exponential stability and -gain analysis are developed in the form of LMIs by using a discontinuous Lyapunov–Krasovskii functional approach. Moreover, the corresponding results can be further extended to more general cases, where the system matrices of the considered plant contain parameter uncertainties, represented in either polytopic or norm-bounded frameworks. In addition, as a special case, we also present the exponential stability, -gain analysis, and the control feedback gain design of event-triggered NCSs without considering the effects of network-induced delays and event-triggering condition in the controller side. Finally, a simulation example is provided to illustrate the usefulness and effectiveness of the proposed hybrid event-triggering *** © 2012 John Wiley & Sons, Ltd.

关键词： event-triggering exponential stability -gain Lyapunov–Krasovskii functional NCSs

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Approximate Jacobian control of robot manipulators without joint velocity measurements

Approximate Jacobian control of robot manipulators without j...

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IEEE International Conference on Cyber Technology in Automation,control,and intelligent Systems

作者： Liang, Xinwu Huang, Xinhan Wang, Min Key Laboratory of Image Processing and Intelligent Control Dept. of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9781612849102

So far, all of the approximate Jacobian controllers for robot manipulators proposed in the literatures have assumed that the exact joint velocity measurements are available. In this paper, we propose alternative controller designs without the use of joint velocity measurements. To provide the joint velocities used by the controllers, we introduce the well-known sliding mode observers to estimate the robot manipulator states. In addition, Lyapunov analysis is presented to show that the combined controller-observer designs can achieve asymptotical stability in the sliding patch. Simulation results are also presented to show the performance of the proposed methods. © 2011 IEEE.

关键词： Velocity measurement

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NEAT versus PSO for evolving autonomous multi-agents coordination on pursuit-evasion problem

NEAT versus PSO for evolving autonomous multi-agents coordin...

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2011 3rd International Asia Conference on Informatics in control, Automation and Robotics, CAR 2011

作者： Zhao, Jin Peng, Gang Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry China

ISBN: (纸本)9783642259913

A method based on multi-agents and ANN (Artificial Neural Network) was proposed to solve the pursuit-evasion task in continuous time-varying environment. According to this method, several autonomous agents with 8 circular sector sensors and an ANN controller were used to form a coordinated behavior to capture the evaders. To evolve the controller, NEAT (NeuroEvolution of Augmenting Topologies) and PSO (Particle Swarm Optimization) method were used to optimize the network. The simulation experiments show that both methods can successfully evolve the controller to capture the evaders, while NEAT requires less swarm members and consume less time comparing to PSO method. © 2011 Springer-Verlag.

关键词： controllers

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Voxel-based treatment prediction of glioblastoma multiform tumor using diffusion tensor imaging

Voxel-based treatment prediction of glioblastoma multiform t...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Hadi Sabahi Hamid Soltanian-Zadeh Lisa Scarpace Tom Mikkelsen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI USA

This paper proposes a method to predict the effect of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The prediction is critical for effective treatment planning. The proposed method is developed and evaluated using Diffusion Tensor Imaging (DTI) and post-contrast T1-weighted Magnetic Resonance images (pc-T1-MRI) of 14 patients with GBM tumors gathered before and after the treatment. First, the proposed method calculates diffusion anisotropy indices (DAI) of all voxels in the brain. These diffusion anisotropy indices are Fractional Anisotropy (FA), Mean Diffusivity (MD), Relative Anisotropy (RA), and Volume Ratio (VR). Then, it registers post-treatment pc-T1-MRI and pre-treatment DAI maps to pre-treatment pc-T1-MRI. Next, it uses a thresholding method to segment the tumor from pc-T1-MRI studies. Comparing Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI, the DAIs of the tumor are labeled based on their response to the treatment. The voxels of 7 patients are randomly selected to train 4 classifiers (ANN, SVM, KNN, and ANFIS) and then all voxels of the other 7 patients are used to test them. For each classifier, four performance measures (sensitivity, specificity, positive predictive value, and accuracy) are calculated. Experimental results show that the ANFIS is more accurate than the other classifiers in predicting the treatment response.

关键词： Support vector machines Noise Magnetic resonance imaging Sensitivity Tumors Biomedical imaging Artificial neural networks

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Deformation prediction of landslide based on genetic-simulated annealing algorithm and BP neural network

Deformation prediction of landslide based on genetic-simulat...

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4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Chen, Huangqiong Zeng, Zhigang Department of Control Science and Engineering Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China

ISBN: (纸本)9781612843735

In this paper, a modified method for landslide prediction is presented. This method is based on the back propagation neural network(BPNN), and we use the combination of genetic algorithm and simulated annealing algorithm to optimize the weights and biases of the network. The improved BPNN modeling can work out the complex nonlinear relation by learning model and using the present data. This paper demonstrates that the revised BPNN modeling can be used to predict and calculate landslide deformation, quicken the learning speed of network and improve the predicting precision. Applying this thinking and method into research of some landslide in the Three Gorges reservoir, the validity and practical value of this model can be demonstrated. And it also shows that the dynamic prediction of landslide deformation is very crucial. © 2011 IEEE.

关键词： Landslides

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Cooperative MIMO Channel Modeling and Multi-Link Spatial Correlation Properties

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IEEE Journal on Selected Areas in Communications 2012年第2期30卷 388-396页

作者： Xiang Cheng Cheng-Xiang Wang Haiming Wang Xiqi Gao Xiao-Hu You Dongfeng Yuan Bo Ai Qiang Huo Ling-Yang Song Bing-Li Jiao School of Electronics and Computer Science Peking University Beijing China Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University China Joint Research Institute for Signal and Image Processing School of Engineering & Physical Sciences Heriot-Watt University Edinburgh UK School of Information Science and Engineering South East University Najing China School of Information Science and Engineering Shandong University Jinan China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

In this paper, a novel unified channel model framework is proposed for cooperative multiple-input multiple-output (MIMO) wireless channels. The proposed model framework is generic and adaptable to multiple cooperative MIMO scenarios by simply adjusting key model parameters. Based on the proposed model framework and using a typical cooperative MIMO communication environment as an example, we derive a novel geometry-based stochastic model (GBSM) applicable to multiple wireless propagation scenarios. The proposed GBSM is the first cooperative MIMO channel model that has the ability to investigate the impact of the local scattering density (LSD) on channel characteristics. From the derived GBSM, the corresponding multi-link spatial correlation functions are derived and numerically analyzed in detail.

关键词： MIMO Correlation Channel models Scattering Educational institutions Fading Adaptation models

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ANN-based control method implemented in a Voltage Source Converter for industrial Micro-Grid

ANN-based control method implemented in a Voltage Source Con...

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6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011

作者： Xu, Jinbang Wu, Zhizhuo Yang, Xuan Ye, Jie Shen, Anwen Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Technology Huazhong University of Science and Technology 430074 Wuhan China

ISBN: (纸本)9780769545141

With more and more attention on the grid current harmonic in recent years, many control schemes of the Pulse Width Modulation Voltage Source Converter (PWMVSC) have been investigated. Conventional PI controller has shown limitations such as sensitivity to load and system parameter variation. Even the stability of the system can be threatened under a large and sudden load change. In this paper, the practical situation of a VSC for industrial Micro Grid (MG) is considered and an Artificial neural network (ANN) based control method is employed to solve the problem. Meanwhile, an on-line parameter tuning algorithm is introduced for its advantage of self-tuning and system character identification. The proposed control scheme is verified through simulation based on SABER software. The simulation results have shown the advantage of the proposed method and the performance of the parameter tuning session. © 2011 IEEE.

关键词： Neural networks

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Feature extraction of motor imagery EEG signals based on wavelet packet decomposition

Feature extraction of motor imagery EEG signals based on wav...

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IEEE/Institute of Complex Medical Engineering International Conference on Complex Medical Engineering

作者： Hu, Dingyin Li, Wei Chen, Xi 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

ISBN: (纸本)9781424493241

Feature extraction in brain-computer interface (BCI) work is an important task that significantly affects the success of brain signal classification. In this paper, a feature extraction method of electroencephalographic (EEG) signals based on wavelet packet decomposition (WPD) is used. The coefficients mean of wavelet packet decomposition and wavelet packet energy of special sub-bands are employed as the original features. The Fisher discriminant analysis (FDA) is used to measure the separabilities of those features. The features which had a higher separability will be considered as effective ones and then the final feature vector are formed. A feature vector is obtained by combining the selected features from six channels. Then, the features are classified by using the k-nearest neighbor (k-NN) algorithm. We obtained significant improvement for the speed and accuracy of the classification for data set Ia, which is a typical representative of one kind of BCI competition 2003 data. The classification results have proved the effectiveness of the proposed method. © 2011 IEEE.

关键词： Feature extraction

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