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2009 International Conference on Computational Science and Engineering, CSE '09

作者： Hui, Chen Yufeng, Shi Ye, Wang Yang, Laurence T. Naixue, Xiong Key laboratory of ministry of education for image processing and intelligent control Huazhong University of Science and Technology Wuhan China Department of Computer Science St Francis Xavier University Canada Department of Computer Science Georgia State University Georgia GA United States

ISBN: (纸本)9780769538235

How to make full use of the limited energy available and prolonging the survival time of node is a major concern in research on Wireless Sensor Networks (WSNs). This paper presented an improved approach based on Directed Diffusion Protocol (DDP) which could meet the features of WSN, such as data-oriented, many-to-one transmissions and low energy costs, together with data aggregation mechanisms which emphasized on cascading timeouts, to eliminate the redundancy caused by the transmission of large amounts of data. This modified protocol prohibited the direct forwarding of central nodes, balancing data traffic of different sensors between the source and the sink, and proved to be able of reducing total network flows, energy consumptions and prolonging the lifetime of the network through simulations.

关键词： Sensor nodes

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Texture image segmentation using Brushlet-domain hidden Markov models

Texture image segmentation using Brushlet-domain hidden Mark...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Liu, Fang Yang, Kai Hao, Hongxia Hou, Biao Zhong, Hua School of Computer Science and Technology Xidian University Xi'an Shanxi 710071 China Intelligent Perception and Image Understanding Key Lab. of Ministry of Education of China Xi'an Shanxi 710071 China Intelligent Information Processing Laboratory Xidian University Xi'an Shanxi 710071 China

ISBN: (纸本)9780819478092

By researching the Brushlet domain coefficients of texture images, we found that the distribution of the magnitudes of Brushlet domain coefficients roughly meet rayleigh distribution. And there are correlations between Brushlet coefficients in adjacent scales. Therefore, Rayleigh Mixture Model (RMM) is used to characterize the statistics of the magnitudes of Brushlet coefficients. To capture the inter-scale persistence of Brushlet coefficients, a "four to four" models with markov property is adopted in this paper. On the basis, by combining with the multi-scale Bayesian segmentation method, we propose a multiscale Bayesian texture segmentation algorithm that is based on a Brushlet domain hidden Markov tree (BruHMT) model. The experiment results indicate that our method is feasible and effective. Especially for coarse texture, our method is superior than texture segmentation method using Wavelet domain hidden Markov tree (WHMT) model. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Hidden Markov models

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Decoupling guaranteed cost control of BTT vehicle based on LMI

Decoupling guaranteed cost control of BTT vehicle based on L...

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IEEE International Conference on intelligent Computing and intelligent Systems (ICIS)

作者： Zhixiang Deng Yongji Wang Lei Liu Chuanfeng Li Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424447374;9781424447541

This paper presents a new approach for coupling control problems for norm bounded continuous-time uncertain systems. Firstly, a design of the state feedback decoupling controller is presented. The nominal model could be decoupled completely and the coupling of the actual system would be reduced. Secondly, based on the linear matrix inequality (LMI), combining the guaranteed cost control law with the decoupling control, the state feedback tracking guaranteed cost control law is proposed. Finally, taking BTT vehicle as the research objective, the design procedure of the decoupling guaranteed cost controllers is shown and the final results of the simulation are proved with effectiveness for the proposed design approach.

关键词： Costs Vehicles control systems Uncertain systems Robust control State feedback Linear matrix inequalities Linear feedback control systems Uncertainty Missiles

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Constrained trajectory optimization using migrant particle swarm optimization algorithm

Constrained trajectory optimization using migrant particle s...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Fuqiang Xie Yongji Wang Zongzhun Zheng Da Zhang Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

A novel PSO algorithm, the Migrant Particle Swarm Optimization (Migrant PSO), is presented to solve the trajectory optimization problem in the presence of constraints such as dynamic pressure and overload. Imitating the behaviour of a flock of migrant birds, the Migrant PSO algorithm employs stochastic search method and adaptive linear search method respectively for PSO search spaces including both continuous space and discrete space. In the example of the minimum peak heat rate reentry trajectory optimization for X-33 vehicle model with free terminal time, some key problems such as parameterized method are argued in detail. The simulation results indicate that the Migrant PSO algorithm proves to be able to generate a complete and optimal 3DOF reentry trajectory rapidly.

关键词： Constraint optimization Particle swarm optimization Stochastic processes Ant colony optimization Optimization methods Search methods Space vehicles Pressure control Birds Optimal control

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Rapid trajectory optimization based on Migrant PSO

Rapid trajectory optimization based on Migrant PSO

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IEEE International Conference on intelligent Computing and intelligent Systems (ICIS)

作者： Fuqiang Xie Yongji Wang Chuanfeng Li Dangjun Zhao Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424447374;9781424447541

This paper proposes a rapid trajectory optimization approach using a novel PSO algorithm, the Migrant particle swarm optimization (Migrant PSO). Imitating the behavior of a flock of migrant birds, the Migrant PSO algorithm employs stochastic search method and adaptive linear search method respectively for PSO search spaces including both continuous space and discrete space. In the example of the minimum control energy reentry trajectory optimization for X-33 vehicle model with free terminal time, some key problems such as parameterized method are argued in detail. The simulation results indicate that the Migrant PSO algorithm proves to be able to generate a complete and optimal 3DOF reentry trajectory rapidly.

关键词： Birds Stochastic processes Search methods Optimization methods Space technology Particle swarm optimization Vehicles Design optimization Programmable control Adaptive control

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Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network

Adaptive dynamic inversion robust control for BTT missile ba...

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MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Li, Chuanfeng Wang, Yongji Deng, Zhixiang Wu, Hao Department of Control Science and Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China Luoyang Institute of Science and Technology 90 Wangcheng Avenue Luoyang 471023 China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9780819478078

A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Lyapunov functions

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Study of Double SMO Algorithm Based on Attributes Reduction

Study of Double SMO Algorithm Based on Attributes Reduction

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6th International Symposium on Neural Networks

作者： Chen, Chen Hong, Liu Song, Haigang Chen, Xueguang Hou, TieMin Huazhong Univ Sci & Technol Inst Syst Engn Wuhan 430074 Peoples R China Bas Res Serv Ministry Sci Beijing 100862 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Processing & Intelligent Control Wuhan 430074 Peoples R China

ISBN: (纸本)9783642015090

To solve the classification problem in data mining, this paper proposes double SMO algorithm based on attributes reduction. Firstly attributes reduction deletes irrelevant attributes (or dimensions) to reduce data amount, consequently the total calculation is reduced, the training speed is fastened and Classification mode is easy to understand. Secondly applying SMO algorithm on the sampling dataset to get the approximate separating hyperplane, and then we obtain all the Support vectors of original dataset. Finally again use SMO algorithm on the support vectors to get the final separating hyperplane. It is shown in the experiments that the algorithm reduces the memory space, effectively avoids the noise points' effect on the final separating hyperplane and the precision of the algorithm is better than Decision Tree, Bayesian and Neural Network.

关键词： Data mining Support vector machine Attribute reduction Training algorithm

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Multiobjective social evolutionary algorithm based on multi-agent

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Ruan Jian Xue Bao/Journal of Software 2009年第7期20卷 1703-1713页

作者： Pan, Xiao-Ying Liu, Fang Jiao, Li-Cheng Key Lab. of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China School of Computer Science and Engineering Xidian University Xi'an 710071 China

In this paper, a multi-agent social evolutionary algorithm is proposed for multiobjective optimization problems. It completes the search process by the agent evolution. MOMASEA (multi-agent social evolutionary algorithm for multiobjective) defines the trust degree to denote the historical information of agents, and the neighborhood of agent is confirmed by it. According to the characteristic of multiobjective problems, three evolutionary operators are designed to complete the whole evolutionary process. The experimental results show that MOMASEA has a good convergence to the Pareto set. Furthermore, the analysis of the mode for instructs local environment verified that importing acquaintance net model can speed up the convergence effectively. © by Institute of Software, the Chinese Academy of Sciences.

关键词： Multiobjective optimization

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Path planning using FMM with direction and curvature constrained

Path planning using FMM with direction and curvature constra...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Li, Shidong Ding, Mingyue Cai, Chao Institute for Pattern Recognition and Artificial Intelligence National Lab. for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China Hubei University for Nationalities Enshi Hubei 445000 China College of Life Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

It is difficult to meet both direction and curvature constraints for traditional Fast Marching (FM) method in path planning. Based on adjusting the cost function in Eiknoal equation-the control equation for FM, a new model for computing the integrated cost function was presented in this paper. A relationship formula about curvature radius was obtained and three kinds of adjusting strategies were given;two of them were used to modify the route to meet with the requires of turning constraint in this paper. Experiments showed that the improved model can be used to plan the path with FMM for agent such as unmanned aerial vehicle (UAV) or robot, which is limited to pass through the scene matching areas. And our preliminary experiments demonstrated that the strategies are feasible and efficient to obtain path with certain curvature radius. The model can also be used to represent the problem such as an aircraft flying in a flow field. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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A novel path planning method based on path network

A novel path planning method based on path network

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

ISBN: (纸本)9780819478085

Traditional path planning methods are too slow to meet the real-time requirement in practical applications. In order to solve this problem, an idea of path net was proposed in this paper. The path planning procedure is divided into two steps: network segment planning and segment assembling. The first step was done with Fast Marching Method, including port selection of segment and network segment planning. Second step, the A* searching method was chosen to select segments for assembling. Experiments demonstrated that our method can obtain an optimal route in a few of seconds after the start and goal are given while several minutes are needed for traditional methods. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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