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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Zhan, Yi Ding, Mingyue Xiao, Feng Zhang, Xuming Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

This paper proposes a improved non-local means (NLM) filter for image denoising. Due to the drawback that the similarity is computed based on the noisy image, the traditional NLM method easily generates the artifacts in case of high-level noise. The proposed method first preprocesses the noisy image by Gaussian filter. Then, a moving window at each pixel of the noisy image is chosen as the search window, and meanwhile, a improved calculation method of spatial distance based on the preprocessed image is used for computing the similarity. Finally, combining the improved distance with search window based on the noisy image, the intensity of each pixel is restored as the traditional NLM method. The standard images are used to evaluate restoration performance of the proposed method. Additionally, the application on medical image denoising also demonstrates that our method is practical. © 2011 IEEE.

关键词： image denoising

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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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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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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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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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Denosing 3D ultrasound images by non-local means accelerated by GPU

Denosing 3D ultrasound images by non-local means accelerated...

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Hu, Song Hou, WenGuang Department of Biomedical Engineering HuaZhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China

ISBN: (纸本)9780769546230

In Ultrasound imaging, speckle noise is the most serious problem which affects the performance of images. Non-local mean filter is a nice method to remove the speckle noise, but the algorithm' computational complexity makes it's a highly time-consuming method. In many applications like image-guided surgical intervention, real-time de-noising is required. This paper implements a NLM method accelerated by GPU for real-time denoising of 3D ultrasound images. The experimental results show the proposed accelerated de-noising method is efficient in terms of denoising quality and real-time. © 2011 IEEE.

关键词： image denoising

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Partial differential equation model method based on image feature for denoising

Partial differential equation model method based on image fe...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zhang, Xiaohua Wang, Ran Jiao, L.C. 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

ISBN: (纸本)9781424494040

For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) model is proposed based on image feature for images denoising. The PDE model is adaptive within each region according to the details of the image feature to adjust the size of the diffusion coefficient. So it can be disposed the high gradient noise at the same time better to retain the edge information. We also analyze the performance of the PDE model method. Numerical results show that our algorithm competes favorably with state of the-art TV projection methods to eliminate noise and reduce Gibbs-type artifacts. ©2011 IEEE.

关键词： image denoising

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An unsupervised change detection based on clustering combined with multiscale and region growing

An unsupervised change detection based on clustering combine...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zhang, Xiaohua Wang, Le Jiao, L.C. 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

ISBN: (纸本)9781424494040

In this paper, a novel approach is proposed for unsupervised change detection of multitemporal remote sensing images. The proposed method is able to produce the change detection result on the difference image without a priori assumptions .Firstly, the difference image which is acquired from multitemporal images. Mean shift algorithm is used to reduce noise of difference image and fake change. Then stationary wavelet transform (SWT) is used to extract feature vector of each pixel .The final change detection map is achieved by k-means clustering combined with region growing. The comparisons with the state-of-the-art change detection methods are provided. ©2011 IEEE.

关键词： Change detection

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image retrieval using the modified intersecting cortical model

Image retrieval using the modified intersecting cortical mod...

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Yuan, Wenjin Zhang, Xuming School of Life Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

The intersecting cortical model(ICM) is driven from the pulse-coupled neural networks (PCNN), and a lot of works have been done on it. In this paper, we have proposed a method, which is modified from the PCNN, to retrieval the image. This method uses the iteration times of the ICM as the feature, and we do it repeatedly. So we will get the feature vectors and utilize the features to retrieval the image. And the experimental results have proved the effectiveness of the proposed method. While the proposed method shows some advantages like the feature curves are linear and steady. © 2011 IEEE.

关键词： image retrieval

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