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2013 International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2013

作者： Yuan, Bao Hong Zhang, De Xiang Fu, Kui Zhang, Ling Jun Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9783037858202

In order to accomplish tracking of moving objects requirements, and overcome the defect of occlusion in the process of tracking moving object, this paper presents a method which uses a combination of MeanShift and Kalman filter algorithm. MeanShift object tracking algorithm uses a histogram to describe the color characteristics of an object, and search the location of an image region that the color histogram is closest to the histogram of the object. Histogram similarity is defined in terms of the Bhattacharya coefficient. When the moving object is a large area blocked, the future state of moving object is estimated by Kalman filter. Experimental results verify that the proposed algorithm achieves efficient tracking of moving objects under the confusing situations. © (2013) Trans Tech Publications, Switzerland.

关键词： Kalman filters

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A study on turbo code performance based on AWGN channel

A study on turbo code performance based on AWGN channel

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2013 International Conference on Precision Mechanical Instruments and Measurement Technology, ICPMIMT 2013

作者： Zhu, Peng Zhu, Jun Liu, Xiang Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University No.3 Feixi Rd Hefei 230039 China

Turbo codes have a wide range of applications in 3G mobile communications, deep-sea communications, satellite communications and other power constrained fields. In the paper, the Turbo Code Decoding Principle and several major decoding methods are introduced. Simulations of Turbo code performance under different parameters of AWGN channel are made and the effects of the different interleaving length, the number of iterations, and the decoding algorithm to Turbo code performance are also discussed in AWGN channel. Simulation results show that under the same signal-to-noise ratio, the more the number of iterations is, the longer the sequence of information is, and the more excellent decoding algorithm is, the better the performance of Turbo codes is. © 2013 Trans Tech Publications Ltd, Switzerland.

关键词： Bit error rate

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A recursive information gene selection using improved Laplacian Maximum Margin Criterion

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Journal of Information and Computational Science 2013年第14期10卷 4435-4443页

作者： Wang, Bangyuan Xu, Hongyang Wang, Nian Bao, Wenxia Anhui Economic Management Institute Department Hefei 230059 China Key Laboratory of Intelligent Computer and Signal Processing Ministry of Education Anhui University Hefei 230039 China

Gene selection is an important research topic in pattern recognition and tumor classification. Numerous methods have been proposed, Maximum Margin Criterion (MMC) is one of the famous methods have been proposed to solve the small size samples problem. But, the MMC only considers the global structure of samples. In this article, a novel recursive gene selection criterion named Laplacian Maximum Margin Criterion Recursive Feature Elimination (LMMC-RFE) is proposed to address this issue. The Laplacian within-class scatter matrix and Laplacian between-class scatter matrix can be formulated by the use of LoG weighted matrix to capture the scatter information. The neighboring structure of the withinclass samples is preserving while the samples from different classes are mapped far from each other. The successful application to the Colon dataset, Prostate dataset and Leukemia dataset suggests this proposed method is more efficient and competitive in gene selection. 1548-7741/Copyright © 2013 Binary Information Press.

关键词： Feature extraction

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Many-Objective evolutionary algorithms for the characteristics of text in the email text categorization

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International Journal of Applied Mathematics and Statistics 2013年第14期44卷 357-364页

作者： Zou, Juan Zheng, Jinhua Deng, Cheng Hu, Weiping Information Engineering College of Xiangtan University Xiangtan Hunan China Key Laboratory of Intelligent Computing and Information Processing Xiangtan University Ministry of Education Xiangtan Hunan China

This paper use the characteristics of text in the email text categorization propose a method of feature word extraction based on many-objective evolutionary algorithms. This method fully considers the semantic characteristics between different feature words, by increasing the many-objective evolutionary algorithms to calculate the feature words, using the fuzzy theory to process the synonyms Compare the test results show that this method not only reduces the dimension of feature word, but also improves the classification accuracy and recall rate, thereby improves the overall performance of the classification system. And make the system reach a higher level of automation and strong portability. © 2013 by CESER Publications.

关键词： Extraction

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Sinc-Chebyshev collocation method for a class of fractional diffusion-wave equations

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The Scientific World Journal 2014年第1期2014卷 143983-143983页

作者： Mao, Zhi Xiao, Aiguo Yu, Zuguo Shi, Long Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China Mathematics and Information Engineering Department Tongren University Tongren Guizhou 554300 China

This paper is devoted to investigating the numerical solution for a class of fractional diffusion-wave equations with a variable coefficient where the fractional derivatives are described in the Caputo sense. The approach is based on the collocation technique where the shifted Chebyshev polynomials in time and the sinc functions in space are utilized, respectively. The problem is reduced to the solution of a system of linear algebraic equations. Through the numerical example, the procedure is tested and the efficiency of the proposed method is confirmed. © 2014 Zhi Mao et al.

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An improved generalized K-L transform and applications in image compression

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Journal of Information and Computational Science 2013年第1期10卷 167-173页

作者： Shi, Yuexiang Tao, Zhiping Gong, Ping Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China School of Information Engineering Xiangtan University Xiangtan 411105 China

Though K-L transform is an optimum transform for image compression based on minimum mean-squared error, its matrix transform differentiates according to the images and the calculation is heavy and difficult. Some papers have proposed the transform based on the matrix K-L transform which was proved faster than K-L transform from tens to hundreds of times with the same level of peak signal-to-noise ratio. As the matrix K-L transform doesn't eliminate the inner correlations of transformed matrix row vectors and this thesis presents to reuse Matrix K-L Transform (MKLT) after the transformed matrix being transposed. As proved by experiments, this method works better at image compression and calculates faster than K-L transform tens to hundreds of times. © 2013 by Binary Information Press.

关键词： Image compression

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Optimal Tracking Control for Ship Course Using Approximate Dynamic Programming Method

Optimal Tracking Control for Ship Course Using Approximate D...

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第三十二届中国控制会议

作者： XIE Qingqing LUO Bin TAN Fuxiao School of Computer Science and Technology Anhui University Key Laboratory of Intelligent Computing ＆ Signal Processing Ministry of EducationAnhui University School of Computer and Information Fuyang Teachers college

ISBN: (纸本)9781479900305

Dynamic programming(DP) is not a useful tool for solving many control problems because of its complexity in computation. In this paper,we propose Approximate Dynamic Programming(ADP) optimal control strategy for ship course trajectory tracking control *** system transformation,we convert the optimal tracking problem into designing a infinite-horizon optimal regulator for the tracking error ***-dependent Heuristic Dynamic programming(ADHDP) technique,as one form of ADR is presented to obtain the infinite-horizon optimal tracking *** the ship course optimal tracking control simulation results,we can see that the ADHDP controller makes the performance index and the control sequence for the error dynamics converge to the optimal *** BP neural networks are used as parametric structures to implement ADHDP *** two neural networks aim at approximating the cost function and the control law,respectively.

关键词： Optimal Tracking Control Approximate Dynamic Programming ADHDP Ship Course

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Novel non-convex online algorithms for robust ranking

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Journal of Information and Computational Science 2013年第17期10卷 5743-5759页

作者： Cheng, Fan Wang, Xufa Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China School of Computer Anhui University Hefei 230039 China School of Computer University of Science and Technology of China Hefei 230027 China

Recently increasing attention has been focused on learning to rank, which aims to learn a ranking function from a set of training data with relevance labels. Many of the ranking algorithms are based on the pairwise preference framework. However, one disadvantage of pairwise ranking is that it is sensitive to the outliers. To tackle the problem, in this paper, we propose two novel online algorithms based on non-convex Ramp Loss which can suppress the influence of outliers. The first one directly defines a new objective function based on Ramp Loss. Considering that the objective function is non-convex, we use the Concave-convex Procedure (CCCP) for convex approximation, then design an online algorithm based on Dual Coordinate Descend Method to learn the final ranking model. The second algorithm applies selective sampling technology in the training phase. It ignores the instances that lie in the flat region of the Ramp Loss in advance, before they are processed by the learner. Experimental results show that the algorithms we proposed have significant robustness to outliers and yield better generalization performance than the baseline rankers, and the results also prove that our algorithms have less computational running time for their less support vectors. © 2013 Binary Information Press.

关键词： Approximation algorithms

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Image bag generator based on bag of visual words

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Journal of Information and Computational Science 2013年第5期10卷 1453-1462页

作者： Zhao, Shu Xu, Chao Xu, Xiansheng Xu, Chenchu Zhang, Yanping Ye, Hong School of Computer Science and Technology Anhui University Hefei 230039 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China Insurance Office Anhui Provincial Hospital Hefei 230001 China

Multi-instance learning is a good tool to deal with the ambiguity of image in Content-based Image Retrieval (CBIR). According to some researchers' work, image bag generator which transforms an image into an instance bag plays an important role in applying multi-instance learning for CBIR. In this paper, the bag generator based on bag of visual words, named Vdbag, is proposed. First, it extracts local features of image from all images, and then it obtains a set of visual words called visual vocabulary by clustering local features where each local cluster's center is a visual word. Our work mainly includes (1) We introduce bag of visual words into image bag generator. (2) We give a reasonable description to express the instance in an image bag. We add the frequency of each visual word as the last dimension of this visual word to construct the corresponding instance. Experimental results with Corel image database show that the proposed method could achieve better precision than that of some existing bag generators. © 2013 Binary Information Press.

关键词： Content based retrieval

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Video Summarization by Robust Low-Rank Subspace Segmentation

Advances in Intelligent Systems and Computing

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Advances in intelligent Systems and computing 2013年 212卷 929-937页

作者： Tu, Zhengzheng Sun, Dengdi Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China School of Computer Science and Technology Anhui University Hefei 230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province Hefei 230039 China

ISBN: (纸本)9783642375019

Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper. Firstly, video frames are represented as multi-dimensional vectors, and then embedded into a group of affine subspaces using low-rank representation according to the content similarity of the frames in the same subspace. Secondly, a series of subspaces are segmented based on the Normalized Cuts algorithm. The video summary is finally generated by choosing key frames from the significant subspaces and ranking these key frames in temporal order. The experimental results demonstrate that the proposed summarization algorithm can produce crucial key frames and effectively reduce the visual content redundancy in summary comparing with the conventional approaches. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Vectors

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