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检索条件"机构=Key Lab.for Image Processing and Intelligent Control"

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A comparative study of radial basis function neural networks in dynamic clustering algorithm

A comparative study of radial basis function neural networks...

引用

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

作者： Zhou, Peng Li, Dehua Wu, Hong Zeng, Jun Chen, Feng State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper developed two learning procedure, respectively, based on the orthogonal least squares (OLS) method and the "Innovation- Contribution" criterion (ICc) proposed newly. The orthogonal use of the stepwise-regression algorithm of the ICc mages the model structure independent of the selected term sequence and reduces the cluster region further as compared with orthogonal least squares (OLS). as the Bayesian information criteria (BIC) method is incorporate into the clustering process of the ICc, except for the widths of Gaussian functions, it has no other parameter that need tuning ,but the user is required to specify the tolerance ρ, which is relevant to noises and will be difficult to implement in the real system, for the OLS algorithm. The two algorithms are employed to the Radial Basis Function Neural Networks (RBFNN) to compare its performance for different noise nonlinear dynamic systems. Experimental results show that they provide an efficient approximation to the required results for fitting models, but the clustering procedures of the ICc is substantially better solutions than does the OLS. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Radial basis function networks

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Epidemic spreading with variant infection rates on scale-free network

引用

6th International Symposium on Neural Networks, ISNN 2009

作者： Hong, Liu Ouyang, Min Mao, Zijun Chen, Xueguang Institute of System Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)3642015123

In this paper, we proposed a susceptible-infected model with variant infection rates because different individuals have different resistance to diseases in different periods of real epidemic events. We consider two cases: Case 1, we know every individual's infection rate to a kind of epidemic, satisfy a type of distribution. Case 2, assume all individuals have same initial infection rates, a susceptible individual's infection rate will be less than the initial rate if he is not infected after limited number of contacts with infected ones. For both two cases, at the time tD, preventive and control measures bring into effects, every individual's infection rate would decrease. We implemented this models on scale-free networks, and found that the epidemic process before the time tD in Case 1 is almost the same as that in Standard SI model if the infection rate in Standard SI model equals the mean infection rate in Case 1. Furthermore, using numerical simulation, we analysis the effects of the parameter tD, and find the bimodal distribution of final infection rates. Finally, we conclude what we get in this paper and give our future direction. © 2009 Springer Berlin Heidelberg.

关键词： Complex networks

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Interdependency analysis of infrastructures

引用

6th International Symposium on Neural Networks, ISNN 2009

作者： Mao, Zijun Hong, Liu Fei, Qi Ouyang, Ming Institute of System Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)3642015123

Electric power, potable water, telecommunications, natural gas, and transportation are examples of critical infrastructures, the intrinsic feature of which are suitable for network analysis. This paper proposes a method framework based on the complex network to explore the interdependency of these infrastructures. We describe the topological characterization of two interdependent small-sized real networks, based on which the interdependent model is devised. We define the interdependent factor to characterize the direct interdependency of two infrastructures, and also its fluctuation in the situations of random removal and targeted removal on the electric and water infrastructures is studied. Furthermore we propose a matrix M to reflect all direct and indirect interactions among infrastructures, which also makes contributions to the understanding of infrastructures catastrophes. © 2009 Springer Berlin Heidelberg.

关键词： Complex networks

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A point-pattern matching method based on maximal subset of one-to-one mapping

A point-pattern matching method based on maximal subset of o...

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

作者： Hu, Jing Zhang, Tian-Xu Institute for Pattern Recognition and AI Hua Zhong University of Science and Technology Wuhan 430074 China Key Lab. of Education Ministry for Image Processing and Intelligent Control Hua Zhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper presents a new affine registration approach for planar point pattern matching. A process of parameter space clustering is implemented to confirm a one-to-one mapping between the maximal subsets of feature point sets in images. For a best performance, a coarse parameter space and a fine parameter space are used for vectors comparison. Experiments show that the method can produce positive results from a small number of feature points and intensive noise. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Affine transforms

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Sliding Mode Tracking for Actuators Comprising Pneumatic Muscle and Torsion Spring

Sliding Mode Tracking for Actuators Comprising Pneumatic Mus...

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2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

作者： Kexin Xing Jian Huang Yongji Wang Jiping He Qi Xu Jun Wu Key Lab.of Image Processing and Intelligent Control Department of Control Science and TechnologyHuazhong University of Science and TechnologyWuhanChina

ISBN: (纸本)9781424447749;9781424447756

In this study, the sliding mode approach is applied to the tracking control problem of a planar arm manipulator system driven by a new type of actuator, which comprises a pneumatic muscle (PM) and a torsion spring. Unlike the traditional agonist/antagonist pneumatic muscle actuator, the PM is arranged in place of bicep and the torsion spring provides opposing torque in the presented actuator. The dynamic model is derived for this system and a sliding mode controller is designed to make the joint angle track a desired trajectory within a guaranteed accuracy even there are modeling uncertainties. A selection method is also proposed to obtain appropriate spring coefficient, which plays an important role in the tracking control task. The effectiveness of the proposed method is confirmed by simulations. The differences between the control results of using our new actuator and that of using the traditional pneumatic muscle actuator in opposing pair configuration are also compared.

关键词： Pneumatic muscle (PM) torsion spring sliding mode control rehabilitation robot

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Study of Double SMO Algorithm Based on Attributes Reduction

Study of Double SMO Algorithm Based on Attributes Reduction

引用

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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Skeleton-based fast path planning for UAV

Skeleton-based fast path planning for UAV

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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, Xin Zhou, Chengping 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 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

A new path planning method for UAV in static workspace is presented. The method can find a nearly optimal path in short time which satisfies the UAV kinematic constraints. The method makes use of the skeletons to construct the graph of the planning space considering the configuration of the obstacles and utilizes the graph to find a shortest collision-free path, and a novel technique is utilized to convert the free path into a feasible path. The method can be applied to different applications and easy to be implemented. Experimental results showed that the path planning can be done in a fraction of second on a contemporary workstation (2-3 seconds) under the condition of satisfying the kinematic constraints. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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Path planning using FMM with direction and curvature constrained

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

引用

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

引用

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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Computer Aided Diagnosis of Fatty Liver Ultrasonic images Based on Support Vector Machine

Computer Aided Diagnosis of Fatty Liver Ultrasonic Images Ba...

引用

30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Li, Guokuan Luo, Yu Deng, Wei Xu, Xiangyang Liu, Aihua Song, Enmin Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China Minist Educ Key Lab Image Processing & Intelligent Control Wuhan 430074 Peoples R China Sixth Hosp Ultrasound Dept Wuhan Peoples R China

ISBN: (纸本)9781424418145

B-scan ultrasound is the primary means for the diagnosis of fatty liver. However, due to use of various ultrasound equipments, poor quality of ultrasonic images and physical differences of patients, fatty liver diagnosis is mainly qualitative, and often depends on the subjective judgment of technicians and doctors. Therefore, computer-aided feature extraction and quantitative analysis of liver B-scan ultrasonic images will help to improve clinical diagnostic accuracy, repeatability and efficiency, and could provide a measure for severity of hepatic steatosis. This paper proposed a novel method of fatty liver diagnosis based on liver B-mode ultrasonic images using support vector machine (SVM). Fatty liver diagnosis was transformed into a pattern recognition problem of liver ultrasound image features. According to the different characteristics of fatty liver and healthy liver, important image features were extracted and selected to distinguish between the two categories. These features could be represented by near-field light-spot density, near-far-field grayscale ratio, grayscale co-occurrence matrix, and neighborhood gray-tone difference matrix (NGTDM). A SVM classifier was modeled and trained using the clinical ultrasound images of both fatty liver and normal liver. It was then exploited to classify normal and fatty livers, achieving a high recognition rate. The diagnostic results are satisfactorily consistent with those made by doctors. This method could be used for computer-aided diagnosis of fatty liver, and help doctors identify the fatty liver ultrasonic images rapidly, objectively and accurately.

关键词： fatty liver B-scan ultrasound grayscale co-occurrence matrix SVM feature extraction

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