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2012 International Conference on Modelling,Identification and control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Chang Liu Xinhan Huang Min Wang Key Laboratory of Image Processing and Intelligent Control of Ministry of Education of China Departm Key Laboratory of Image Processing and IntelligentControl of Ministry of Education of China Departme

Visual servoing has been around for decades, but the time delay is still one of the most troublesome problems to achieve maneuvering target *** circumvent the problem, in this paper, the Kalman filter is employed to estimate future position of the maneuvering *** order to introduce the Kalman filter, the accurate time delays, which include the processing lag and the motion lag, need to be ***, the delays of the visual control servoing systems are discussed, and a generic timing model for the system are ***, we present a current statistical model for maneuvering *** adaptive Kalman filter, which is evolved from the Kalman filter, is put forward based on the current statistical *** results show that the modified adaptive filter can improve the ability of maneuvering target tracking.

关键词： Kalman filter Timing Model Target Tracking Micro Maniputlation

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Model Reference Decoupling controller Design via LMI Optimization

Model Reference Decoupling Controller Design via LMI Optimiz...

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2012 International Conference on Modelling,Identification and control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Lei Liu Zhishen Wang Zongzhun Zheng Yongji Wang Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of C Beijing Aerospace Automatic Control Institute BeijingChina Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of C

This paper proposed a H∞ based controller design method for MIMO *** use the bound real lemma to design the controller when the reference model is *** BMI (Bi-linear Matrix Inequality) problem is turned into a LMI (Linear Matrix Inequality) problem by congruence transformation and variables *** a decoupled reference model, the decoupling controller can be obtained by *** apply the method to a linearized vehicle model and the simulation results show the effectiveness of the approach.

关键词： decoupling linear matrix inequality H-infinity (H∞) model reference control

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The application of support vector machines and improved particle swarm optimization

The application of support vector machines and improved part...

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Zhang, Hu Wang, Min Huang, Xinhan Key Laboratory of Image Processing and Intelligent Control of Education Department of Control Science and Engineering Huazhong University of Science and Technology NO.1037 Luoyu Road 430074 Wuhan China

ISBN: (纸本)9780956715715

Parameters selection of support vector machine is the key issue that impacts its accurate performance. A method for support vector regression machine with standard particle swarm optimization (SPSO) algorithm is proposed in this paper. Furthermore, in order to improve the performance of the SPSO algorithm, the concept of the particles' average distance and fitness variance is proposed to make the efficiency of algorithm better. So, the improve algorithm was also applied in this paper. The two different models using SPSO and IPSO respectively were used to forecast the density of the acid-lead battery electrolyte. The experimental results indicate that both SPSO and IPSO have high prediction accuracy and efficiency. The time of the parametric searching by IPSO is obviously decreased to that of SPSO. The mean squared error (MSE) of the prediction model using SPSO is about 2.02056×10-4, Meanwhile, the MSE of the model using IPSO is only about 1.9324×10-4. So, the IPSO algorithm has more superior performance on convergence speed and global optimization. © 2012 Huazhong Univ of Sci & Tec.

关键词： Support vector machines

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Dynamic Ca2+ sensitivity of BK channels

Dynamic Ca2+ sensitivity of BK channels

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The 4th International Ion Channel Conference(第四届国际离子通道会议)

作者： Panpan Hou Jianming Cui Ding Jiuping Feng Xiao Ming Yuchi Guohui Zhang Ying Wu Wei Wang Wenping Zeng Mingyue Ding Zhengxing Wu Department of pharmacology Soochow University college of pharmaceutical Sciences SuzhouChina Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Department of Biomedical Engineering College of Life Science and Technology Wuhan China Department of Biomedical Engineering Center for the Investigation of Membrane Excitability Disorders Cardiac Bioelectricity and Arrhythmia Center Washington University St Louis MOUSA Key Laboratory of Molecular Biophysics Huazhong University of Science and Technology Ministry of Education College of Life Science and Technology Wuhan China Department of Biomedical Engineering Center for the Investigation of Membrane Excitability Disorders Cardiac Bioelectricity and Arrhythmia Center Washington University St Louis MOUSA

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Integrating segmentation and classification accuracy for accuracy assessment in object-based image analysis

Integrating segmentation and classification accuracy for acc...

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2012 3rd IEEE/IET International Conference on Audio, Language and image processing, ICALIP 2012

作者： Li, Nan Huo, Hong Fang, Tao Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

ISBN: (纸本)9781467301718

An accuracy assessment method that integrates segmentation and classification accuracy is proposed to meet the requirements of object-based image analysis. Segmentation errors are measured by establishing the relationship between pixels and their corresponding segments according to the overlaps of segments and reference polygons. Then, two improved confusion matrices that take the segmentation errors into consideration are used: one for pixel-level classification results, and the other for object-level classification results. A final accuracy assessment combines the statistics of these two confusion matrices. The proposed method can be applied to segmentation scale selection in the hierarchical interpretation system. An experiment on a SPOT5 image demonstrates the effectiveness of this method for segmentation scale selection, which can guide the fusion of objects of different scales to obtain a higher accuracy. © 2012 IEEE.

关键词： image analysis

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Adaptive multi-feature tracking in particle swarm optimization based particle filter framework

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Journal of Systems Engineering and Electronics 2012年第5期23卷 775-783页

作者： Miaohui Zhang Ming Xin Jie Yang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 P. R. China Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 P. R. China

This paper proposes a particle swarm optimization（PSO） based particle filter（PF） tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state transition stage,and simultaneously incorporates the newest observations into the proposal distribution in the update *** the proposed approach,likelihood measure functions involving multiple features are presented to enhance the performance of model ***,the multi-feature weights are self-adaptively adjusted by a PSO algorithm throughout the tracking *** are three main ***,the PSO algorithm is fused into the PF framework,which can efficiently alleviate the particles degeneracy ***,an effective convergence criterion for the PSO algorithm is explored,which can avoid particles getting stuck in local minima and maintain a greater particle ***,a multi-feature weight self-adjusting strategy is proposed,which can significantly improve the tracking robustness and *** performed on several challenging public video sequences demonstrate that the proposed tracking approach achieves a considerable performance.

关键词： particle filter particle swarm optimization adaptive weight adjustment visual tracking

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The application of support vector machines and improved particle swarm optimization

The application of support vector machines and improved part...

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2012 International Conference on Modelling,Identification and control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Hu Zhang Min Wang Xinhan Huang Key Laboratory of Image Processing and Intelligent Control of Education Department of Control Scienc Key Laboratory of Image Processing and IntelligentControl of Education Department of Control Science Key Laboratory of Image Processing andIntelligent Control of Education Department of Control Science

ISBN: (纸本)9781467315241

Parameters selection of support vector machine is the key issue that impacts its accurate performance.A method for support vector regression machine with standard particle swarm optimization (SPSO) algorithm is proposed in this ***, in order to improve the performance of the SPSO algorithm, the concept of the particles’ average distance and fitness variance is proposed to make the efficiency of algorithm ***, the improve algorithm was also applied in this *** two different models using SPSO and IPSO respectively were used to forecast the density of the acid-lead battery *** experimental results indicate that both SPSO and IPSO have high prediction accuracy and *** time of the parametric searching by IPSO is obviously decreased to that of *** mean squared error (MSE) of the prediction model using SPSO is about 2.02056×10-4, Meanwhile, the MSE of the model using IPSO is only about 1.9324×***, the IPSO algorithm has more superior performance on convergence speed and global optimization.

关键词： support vector regression particle swarm optimization average particle distance fitness variance

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A Novel Small Dim Infrared Target Detecting Method based on Grayscale Merging and Connected Components Analysis

A Novel Small Dim Infrared Target Detecting Method based on ...

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2012 International Conference on Modelling,Identification and control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Ying Zhang Min Wang Shaoqing Niu Key Laboratory of Image Processing and Intelligent Control of Education Department of Control Scienc Key Laboratory of Image Processing and IntelligentControl of Education Department of Control Science Key Laboratory of Image Processing andIntelligent Control of Education Department of Control Science

Target detecting algorithm in infrared image is drawing extensive attention both at home and abroad, expecially when the infrared images own complex backgrounds and low *** to make sure of the accuracy of infrared dim-small target detecting is the key point during the processing *** this paper, a novel region of interest detecting algorithm is proposed for aerial small dim infrared target with clutter *** from traditional region of interest extraction method, we extract region of interest based on the grayscale merging algorithm and connected components analysising ***, the infrared image is reconstructed by separating the grayscale into several interval sections, then binarization is used to segment the processed image according to estimate the threshold value using minimum error probability;finally, analysis and select the connected components, to sift the accurate connected domain which contain the *** validity of the proposed approach is demonstrated by experiment of infrared target region extraction.

关键词： Infrared small-dim target object detection connected component minimum error probability

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Study on landslide deformation prediction based on recurrent neural network under the function of rainfall

Study on landslide deformation prediction based on recurrent...

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19th International Conference on Neural Information processing, ICONIP 2012

作者： Chen, Huangqiong Zeng, Zhigang Tang, Huiming Department of Control Science and Engineering 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 Faculty of Engineering China University of Geosciences Wuhan Hubei 430074 China

ISBN: (纸本)9783642344770

Landslide deformation prediction has significant practical value that can provide guidance for preventing the disaster and guarantee the safety of people's life and property. In this paper, a method based on recurrent neural network (RNN) for landslide prediction is presented. The results show that the prediction accuracy of RNN model is much higher than the feedforward neural network model for Baishuihehe landslide. Therefore, the RNN model is an effective and feasible method to further improve accuracy for landslide displacement prediction. © 2012 Springer-Verlag.

关键词： Recurrent neural networks

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Propagation effects of low frequency electromagnetic waves in production well

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Petroleum Science 2012年第2期9卷 182-191页

作者： Song Xijin Guo Baolong Dang Ruirong Wang Xuelong Institute of Intelligent Control and Image Engineering Xidian UniversityShaanxi 710071China Key Laboratory of Photoelectric Logging and Detecting of Oil and Gas Ministry of EducationXi'an Shiyou UniversityShaanxi 710065China College of Computer Science&Technology Shaanxi University of TechnologyShaanxi 710048China

The frequency domain electromagnetic method has already been widely used for tomographic imaging or electromagnetic well logging. However, different from open hole logging, the metal casing existing in production well logging has a strong shielding effect on the electromagnetic waves, thus bringing some difficulties to the application of the frequency domain electromagnetic method in production well logging. According to the relation of the field source geometry to the ring around the mandrel, the general expressions of frequency domain electromagnetic responses in axially symmetrical layered conductive medium are deduced. The propagation effects caused by the low-frequency electromagnetic waves in cased hole are also analyzed. The distribution curves of eddy current density and magnetic flux density along the radial direction in the mandrel indicate that the eddy loss within the mandrel is proportional to the transmission signal frequency and the mandrel conductivity. The secondary field responses of different casing materials show that the transmission frequency has an important effect on the ability of electromagnetic waves penetrating the metal casing. The transmission frequency should be ultra-low in order to enable the electromagnetic signal to penetrate the casing easily. The numerical results of frequency responses for different casing physical parameters show that the casing thickness has a significant impact on the choice of the transmission frequency. It is also found that the effect of the casing radius on the transmission frequency can be neglected.

关键词： Propagation effects eddy current density magnetic flux density production well frequency response

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